Header logo is


2018


Thumb xl teaser image
Probabilistic Recurrent State-Space Models

Doerr, A., Daniel, C., Schiegg, M., Nguyen-Tuong, D., Schaal, S., Toussaint, M., Trimpe, S.

In Proceedings of the International Conference on Machine Learning (ICML), International Conference on Machine Learning (ICML), July 2018 (inproceedings)

Abstract
State-space models (SSMs) are a highly expressive model class for learning patterns in time series data and for system identification. Deterministic versions of SSMs (e.g., LSTMs) proved extremely successful in modeling complex time-series data. Fully probabilistic SSMs, however, unfortunately often prove hard to train, even for smaller problems. To overcome this limitation, we propose a scalable initialization and training algorithm based on doubly stochastic variational inference and Gaussian processes. In the variational approximation we propose in contrast to related approaches to fully capture the latent state temporal correlations to allow for robust training.

am ics

arXiv pdf Project Page [BibTex]

2018


arXiv pdf Project Page [BibTex]


Thumb xl meta learning overview
Online Learning of a Memory for Learning Rates

(nominated for best paper award)

Meier, F., Kappler, D., Schaal, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2018, IEEE, International Conference on Robotics and Automation, May 2018, accepted (inproceedings)

Abstract
The promise of learning to learn for robotics rests on the hope that by extracting some information about the learning process itself we can speed up subsequent similar learning tasks. Here, we introduce a computationally efficient online meta-learning algorithm that builds and optimizes a memory model of the optimal learning rate landscape from previously observed gradient behaviors. While performing task specific optimization, this memory of learning rates predicts how to scale currently observed gradients. After applying the gradient scaling our meta-learner updates its internal memory based on the observed effect its prediction had. Our meta-learner can be combined with any gradient-based optimizer, learns on the fly and can be transferred to new optimization tasks. In our evaluations we show that our meta-learning algorithm speeds up learning of MNIST classification and a variety of learning control tasks, either in batch or online learning settings.

am

pdf video code [BibTex]

pdf video code [BibTex]


Thumb xl learning ct w asm block diagram detailed
Learning Sensor Feedback Models from Demonstrations via Phase-Modulated Neural Networks

Sutanto, G., Su, Z., Schaal, S., Meier, F.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2018, IEEE, International Conference on Robotics and Automation, May 2018 (inproceedings)

am

pdf video [BibTex]

pdf video [BibTex]


no image
Enhanced Non-Steady Gliding Performance of the MultiMo-Bat through Optimal Airfoil Configuration and Control Strategy

Kim, H., Woodward, M. A., Sitti, M.

In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 1382-1388, 2018 (inproceedings)

pi

[BibTex]

[BibTex]


no image
On Time Optimization of Centroidal Momentum Dynamics

Ponton, B., Herzog, A., Del Prete, A., Schaal, S., Righetti, L.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 5776-5782, IEEE, Brisbane, Australia, 2018 (inproceedings)

Abstract
Recently, the centroidal momentum dynamics has received substantial attention to plan dynamically consistent motions for robots with arms and legs in multi-contact scenarios. However, it is also non convex which renders any optimization approach difficult and timing is usually kept fixed in most trajectory optimization techniques to not introduce additional non convexities to the problem. But this can limit the versatility of the algorithms. In our previous work, we proposed a convex relaxation of the problem that allowed to efficiently compute momentum trajectories and contact forces. However, our approach could not minimize a desired angular momentum objective which seriously limited its applicability. Noticing that the non-convexity introduced by the time variables is of similar nature as the centroidal dynamics one, we propose two convex relaxations to the problem based on trust regions and soft constraints. The resulting approaches can compute time-optimized dynamically consistent trajectories sufficiently fast to make the approach realtime capable. The performance of the algorithm is demonstrated in several multi-contact scenarios for a humanoid robot. In particular, we show that the proposed convex relaxation of the original problem finds solutions that are consistent with the original non-convex problem and illustrate how timing optimization allows to find motion plans that would be difficult to plan with fixed timing † †Implementation details and demos can be found in the source code available at https://git-amd.tuebingen.mpg.de/bponton/timeoptimization.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Collectives of Spinning Mobile Microrobots for Navigation and Object Manipulation at the Air-Water Interface

Wang, W., Kishore, V., Koens, L., Lauga, E., Sitti, M.

In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 1-9, 2018 (inproceedings)

pi

[BibTex]

[BibTex]


no image
Endo-VMFuseNet: A Deep Visual-Magnetic Sensor Fusion Approach for Endoscopic Capsule Robots

Turan, M., Almalioglu, Y., Gilbert, H. B., Sari, A. E., Soylu, U., Sitti, M.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 1-7, 2018 (inproceedings)

pi

[BibTex]

[BibTex]


no image
Endosensorfusion: Particle filtering-based multi-sensory data fusion with switching state-space model for endoscopic capsule robots

Turan, M., Almalioglu, Y., Gilbert, H., Araujo, H., Cemgil, T., Sitti, M.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 1-8, 2018 (inproceedings)

pi

[BibTex]

[BibTex]


no image
Unsupervised Contact Learning for Humanoid Estimation and Control

Rotella, N., Schaal, S., Righetti, L.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 411-417, IEEE, Brisbane, Australia, 2018 (inproceedings)

Abstract
This work presents a method for contact state estimation using fuzzy clustering to learn contact probability for full, six-dimensional humanoid contacts. The data required for training is solely from proprioceptive sensors - endeffector contact wrench sensors and inertial measurement units (IMUs) - and the method is completely unsupervised. The resulting cluster means are used to efficiently compute the probability of contact in each of the six endeffector degrees of freedom (DoFs) independently. This clustering-based contact probability estimator is validated in a kinematics-based base state estimator in a simulation environment with realistic added sensor noise for locomotion over rough, low-friction terrain on which the robot is subject to foot slip and rotation. The proposed base state estimator which utilizes these six DoF contact probability estimates is shown to perform considerably better than that which determines kinematic contact constraints purely based on measured normal force.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Learning Task-Specific Dynamics to Improve Whole-Body Control

Gams, A., Mason, S., Ude, A., Schaal, S., Righetti, L.

In Hua, IEEE, Beijing, China, November 2018 (inproceedings)

Abstract
In task-based inverse dynamics control, reference accelerations used to follow a desired plan can be broken down into feedforward and feedback trajectories. The feedback term accounts for tracking errors that are caused from inaccurate dynamic models or external disturbances. On underactuated, free-floating robots, such as humanoids, high feedback terms can be used to improve tracking accuracy; however, this can lead to very stiff behavior or poor tracking accuracy due to limited control bandwidth. In this paper, we show how to reduce the required contribution of the feedback controller by incorporating learned task-space reference accelerations. Thus, we i) improve the execution of the given specific task, and ii) offer the means to reduce feedback gains, providing for greater compliance of the system. With a systematic approach we also reduce heuristic tuning of the model parameters and feedback gains, often present in real-world experiments. In contrast to learning task-specific joint-torques, which might produce a similar effect but can lead to poor generalization, our approach directly learns the task-space dynamics of the center of mass of a humanoid robot. Simulated and real-world results on the lower part of the Sarcos Hermes humanoid robot demonstrate the applicability of the approach.

am mg

link (url) [BibTex]

link (url) [BibTex]


no image
An MPC Walking Framework With External Contact Forces

Mason, S., Rotella, N., Schaal, S., Righetti, L.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 1785-1790, IEEE, Brisbane, Australia, May 2018 (inproceedings)

Abstract
In this work, we present an extension to a linear Model Predictive Control (MPC) scheme that plans external contact forces for the robot when given multiple contact locations and their corresponding friction cone. To this end, we set up a two-step optimization problem. In the first optimization, we compute the Center of Mass (CoM) trajectory, foot step locations, and introduce slack variables to account for violating the imposed constraints on the Zero Moment Point (ZMP). We then use the slack variables to trigger the second optimization, in which we calculate the optimal external force that compensates for the ZMP tracking error. This optimization considers multiple contacts positions within the environment by formulating the problem as a Mixed Integer Quadratic Program (MIQP) that can be solved at a speed between 100-300 Hz. Once contact is created, the MIQP reduces to a single Quadratic Program (QP) that can be solved in real-time ({\textless}; 1kHz). Simulations show that the presented walking control scheme can withstand disturbances 2-3× larger with the additional force provided by a hand contact.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]

2017


Thumb xl amd intentiongan
Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets

Hausman, K., Chebotar, Y., Schaal, S., Sukhatme, G., Lim, J.

In Proceedings from the conference "Neural Information Processing Systems 2017., (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., Advances in Neural Information Processing Systems 30 (NIPS), December 2017 (inproceedings)

am

pdf video [BibTex]

2017


pdf video [BibTex]


Thumb xl fig toyex lqr1kernel 1
On the Design of LQR Kernels for Efficient Controller Learning

Marco, A., Hennig, P., Schaal, S., Trimpe, S.

Proceedings of the 56th IEEE Annual Conference on Decision and Control (CDC), pages: 5193-5200, IEEE, IEEE Conference on Decision and Control, December 2017 (conference)

Abstract
Finding optimal feedback controllers for nonlinear dynamic systems from data is hard. Recently, Bayesian optimization (BO) has been proposed as a powerful framework for direct controller tuning from experimental trials. For selecting the next query point and finding the global optimum, BO relies on a probabilistic description of the latent objective function, typically a Gaussian process (GP). As is shown herein, GPs with a common kernel choice can, however, lead to poor learning outcomes on standard quadratic control problems. For a first-order system, we construct two kernels that specifically leverage the structure of the well-known Linear Quadratic Regulator (LQR), yet retain the flexibility of Bayesian nonparametric learning. Simulations of uncertain linear and nonlinear systems demonstrate that the LQR kernels yield superior learning performance.

am ics pn

arXiv PDF On the Design of LQR Kernels for Efficient Controller Learning - CDC presentation DOI Project Page [BibTex]

arXiv PDF On the Design of LQR Kernels for Efficient Controller Learning - CDC presentation DOI Project Page [BibTex]


Thumb xl teaser
Optimizing Long-term Predictions for Model-based Policy Search

Doerr, A., Daniel, C., Nguyen-Tuong, D., Marco, A., Schaal, S., Toussaint, M., Trimpe, S.

Proceedings of 1st Annual Conference on Robot Learning (CoRL), 78, pages: 227-238, (Editors: Sergey Levine and Vincent Vanhoucke and Ken Goldberg), 1st Annual Conference on Robot Learning, November 2017 (conference)

Abstract
We propose a novel long-term optimization criterion to improve the robustness of model-based reinforcement learning in real-world scenarios. Learning a dynamics model to derive a solution promises much greater data-efficiency and reusability compared to model-free alternatives. In practice, however, modelbased RL suffers from various imperfections such as noisy input and output data, delays and unmeasured (latent) states. To achieve higher resilience against such effects, we propose to optimize a generative long-term prediction model directly with respect to the likelihood of observed trajectories as opposed to the common approach of optimizing a dynamics model for one-step-ahead predictions. We evaluate the proposed method on several artificial and real-world benchmark problems and compare it to PILCO, a model-based RL framework, in experiments on a manipulation robot. The results show that the proposed method is competitive compared to state-of-the-art model learning methods. In contrast to these more involved models, our model can directly be employed for policy search and outperforms a baseline method in the robot experiment.

am ics

PDF Project Page [BibTex]

PDF Project Page [BibTex]


no image
A New Data Source for Inverse Dynamics Learning

Kappler, D., Meier, F., Ratliff, N., Schaal, S.

In Proceedings IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, Piscataway, NJ, USA, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2017 (inproceedings)

am

[BibTex]

[BibTex]


no image
Bayesian Regression for Artifact Correction in Electroencephalography

Fiebig, K., Jayaram, V., Hesse, T., Blank, A., Peters, J., Grosse-Wentrup, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference 2017 - From Vision to Reality, pages: 131-136, (Editors: Müller-Putz G.R., Steyrl D., Wriessnegger S. C., Scherer R.), Graz University of Technology, Austria, Graz Brain-Computer Interface Conference, September 2017 (conference)

am ei

DOI [BibTex]

DOI [BibTex]


no image
Investigating Music Imagery as a Cognitive Paradigm for Low-Cost Brain-Computer Interfaces

Grossberger, L., Hohmann, M. R., Peters, J., Grosse-Wentrup, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference 2017 - From Vision to Reality, pages: 160-164, (Editors: Müller-Putz G.R., Steyrl D., Wriessnegger S. C., Scherer R.), Graz University of Technology, Austria, Graz Brain-Computer Interface Conference, September 2017 (conference)

am ei

DOI [BibTex]

DOI [BibTex]


Thumb xl screen shot 2017 08 01 at 15.41.10
On the relevance of grasp metrics for predicting grasp success

Rubert, C., Kappler, D., Morales, A., Schaal, S., Bohg, J.

In Proceedings of the IEEE/RSJ International Conference of Intelligent Robots and Systems, September 2017 (inproceedings) Accepted

Abstract
We aim to reliably predict whether a grasp on a known object is successful before it is executed in the real world. There is an entire suite of grasp metrics that has already been developed which rely on precisely known contact points between object and hand. However, it remains unclear whether and how they may be combined into a general purpose grasp stability predictor. In this paper, we analyze these questions by leveraging a large scale database of simulated grasps on a wide variety of objects. For each grasp, we compute the value of seven metrics. Each grasp is annotated by human subjects with ground truth stability labels. Given this data set, we train several classification methods to find out whether there is some underlying, non-trivial structure in the data that is difficult to model manually but can be learned. Quantitative and qualitative results show the complexity of the prediction problem. We found that a good prediction performance critically depends on using a combination of metrics as input features. Furthermore, non-parametric and non-linear classifiers best capture the structure in the data.

am

Project Page [BibTex]

Project Page [BibTex]


no image
Swimming in low reynolds numbers using planar and helical flagellar waves

Khalil, I. S. M., Tabak, A. F., Seif, M. A., Klingner, A., Adel, B., Sitti, M.

In International Conference on Intelligent Robots and Systems (IROS) 2017, pages: 1907-1912, International Conference on Intelligent Robots and Systems, September 2017 (inproceedings)

Abstract
In travelling towards the oviducts, sperm cells undergo transitions between planar to helical flagellar propulsion by a beating tail based on the viscosity of the environment. In this work, we aim to model and mimic this behaviour in low Reynolds number fluids using externally actuated soft robotic sperms. We numerically investigate the effects of transition between planar to helical flagellar propulsion on the swimming characteristics of the robotic sperm using a model based on resistive-force theory to study the role of viscous forces on its flexible tail. Experimental results are obtained using robots that contain magnetic particles within the polymer matrix of its head and an ultra-thin flexible tail. The planar and helical flagellar propulsion are achieved using in-plane and out-of-plane uniform fields with sinusoidally varying components, respectively. We experimentally show that the swimming speed of the robotic sperm increases by a factor of 1.4 (fluid viscosity 5 Pa.s) when it undergoes a controlled transition between planar to helical flagellar propulsion, at relatively low actuation frequencies.

pi

DOI [BibTex]

DOI [BibTex]


no image
Local Bayesian Optimization of Motor Skills

Akrour, R., Sorokin, D., Peters, J., Neumann, G.

Proceedings of the 34th International Conference on Machine Learning, 70, pages: 41-50, Proceedings of Machine Learning Research, (Editors: Doina Precup, Yee Whye Teh), PMLR, International Conference on Machine Learning (ICML), August 2017 (conference)

am ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


Thumb xl pilqr cover
Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning

Chebotar, Y., Hausman, K., Zhang, M., Sukhatme, G., Schaal, S., Levine, S.

Proceedings of the 34th International Conference on Machine Learning, 70, Proceedings of Machine Learning Research, (Editors: Doina Precup, Yee Whye Teh), PMLR, International Conference on Machine Learning (ICML), August 2017 (conference)

am

pdf video [BibTex]

pdf video [BibTex]


Thumb xl publications toc
An XY ϴz flexure mechanism with optimal stiffness properties

Lum, G. Z., Pham, M. T., Teo, T. J., Yang, G., Yeo, S. H., Sitti, M.

In 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), pages: 1103-1110, July 2017 (inproceedings)

Abstract
The development of optimal XY θz flexure mechanisms, which can deliver high precision motion about the z-axis, and along the x- and y-axes is highly desirable for a wide range of micro/nano-positioning tasks pertaining to biomedical research, microscopy technologies and various industrial applications. Although maximizing the stiffness ratios is a very critical design requirement, the achievable translational and rotational stiffness ratios of existing XY θz flexure mechanisms are still restricted between 0.5 and 130. As a result, these XY θz flexure mechanisms are unable to fully optimize their workspace and capabilities to reject disturbances. Here, we present an optimal XY θz flexure mechanism, which is designed to have maximum stiffness ratios. Based on finite element analysis (FEA), it has translational stiffness ratio of 248, rotational stiffness ratio of 238 and a large workspace of 2.50 mm × 2.50 mm × 10°. Despite having such a large workspace, FEA also predicts that the proposed mechanism can still achieve a high bandwidth of 70 Hz. In comparison, the bandwidth of similar existing flexure mechanisms that can deflect more than 0.5 mm or 0.5° is typically less than 45 Hz. Hence, the high stiffness ratios of the proposed mechanism are achieved without compromising its dynamic performance. Preliminary experimental results pertaining to the mechanism's translational actuating stiffness and bandwidth were in agreement with the FEA predictions as the deviation was within 10%. In conclusion, the proposed flexure mechanism exhibits superior performance and can be used across a wide range of applications.

pi

DOI [BibTex]

DOI [BibTex]


Thumb xl publications toc
Positioning of drug carriers using permanent magnet-based robotic system in three-dimensional space

Khalil, I. S. M., Alfar, A., Tabak, A. F., Klingner, A., Stramigioli, S., Sitti, M.

In 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), pages: 1117-1122, July 2017 (inproceedings)

Abstract
Magnetic control of drug carriers using systems with open-configurations is essential to enable scaling to the size of in vivo applications. In this study, we demonstrate motion control of paramagnetic microparticles in a low Reynolds number fluid, using a permanent magnet-based robotic system with an open-configuration. The microparticles are controlled in three-dimensional (3D) space using a cylindrical NdFeB magnet that is fixed to the end-effector of a robotic arm. We develop a kinematic map between the position of the microparticles and the configuration of the robotic arm, and use this map as a basis of a closed-loop control system based on the position of the microparticles. Our experimental results show the ability of the robot configuration to control the exerted field gradient on the dipole of the microparticles, and achieve positioning in 3D space with maximum error of 300 µm and 600 µm in the steady-state during setpoint and trajectory tracking, respectively.

pi

DOI [BibTex]

DOI [BibTex]


no image
Self-assembly of micro/nanosystems across scales and interfaces

Mastrangeli, M.

In 2017 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), pages: 676 - 681, IEEE, July 2017 (inproceedings)

Abstract
Steady progress in understanding and implementation are establishing self-assembly as a versatile, parallel and scalable approach to the fabrication of transducers. In this contribution, I illustrate the principles and reach of self-assembly with three applications at different scales - namely, the capillary self-alignment of millimetric components, the sealing of liquid-filled polymeric microcapsules, and the accurate capillary assembly of single nanoparticles - and propose foreseeable directions for further developments.

pi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


Thumb xl publications toc
Dynamic analysis on hexapedal water-running robot with compliant joints

Kim, H., Liu, Y., Jeong, K., Sitti, M., Seo, T.

In 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), pages: 250-251, June 2017 (inproceedings)

Abstract
The dynamic analysis has been considered as one of the important design methods to design robots. In this research, we derive dynamic equation of hexapedal water-running robot to design compliant joints. The compliant joints that connect three bodies will be used to improve mobility and stability of water-running motion's pitch behavior. We considered all of parts as rigid body including links of six Klann mechanisms and three main frames. And then, we derived dynamic equation by using the Lagrangian method with external force of the water. We are expecting that the dynamic analysis is going to be used to design parts of the water running robot.

pi

DOI [BibTex]

DOI [BibTex]


Thumb xl apollo system2 croped
Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers

Doerr, A., Nguyen-Tuong, D., Marco, A., Schaal, S., Trimpe, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 5295-5301, IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (inproceedings)

am ics

PDF arXiv DOI Project Page [BibTex]

PDF arXiv DOI Project Page [BibTex]


Thumb xl learning ct block diagram v2
Learning Feedback Terms for Reactive Planning and Control

Rai, A., Sutanto, G., Schaal, S., Meier, F.

Proceedings 2017 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (conference)

am

pdf video [BibTex]

pdf video [BibTex]


Thumb xl this one
Virtual vs. Real: Trading Off Simulations and Physical Experiments in Reinforcement Learning with Bayesian Optimization

Marco, A., Berkenkamp, F., Hennig, P., Schoellig, A. P., Krause, A., Schaal, S., Trimpe, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 1557-1563, IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (inproceedings)

am ics pn

PDF arXiv ICRA 2017 Spotlight presentation Virtual vs. Real - Video explanation DOI Project Page [BibTex]

PDF arXiv ICRA 2017 Spotlight presentation Virtual vs. Real - Video explanation DOI Project Page [BibTex]


Thumb xl publications toc
Design and actuation of a magnetic millirobot under a constant unidirectional magnetic field

Erin, O., Giltinan, J., Tsai, L., Sitti, M.

In Proceedings 2017 IEEE International Conference on Robotics and Automation (ICRA), pages: 3404-3410, IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (inproceedings)

Abstract
Magnetic untethered millirobots, which are actuated and controlled by remote magnetic fields, have been proposed for medical applications due to their ability to safely pass through tissues at long ranges. For example, magnetic resonance imaging (MRI) systems with a 3-7 T constant unidirectional magnetic field and 3D gradient coils have been used to actuate magnetic robots. Such magnetically constrained systems place limits on the degrees of freedom that can be actuated for untethered devices. This paper presents a design and actuation methodology for a magnetic millirobot that exhibits both position and orientation control in 2D under a magnetic field, dominated by a constant unidirectional magnetic field as found in MRI systems. Placing a spherical permanent magnet, which is free to rotate inside the millirobot and located away from the center of mass, allows the generation of net forces and torques with applied 3D magnetic field gradients. We model this system in a 3D planar case and experimentally demonstrate open-loop control of both position and orientation by the applied 2D field gradients. The actuation performance is characterized across the most important design variables, and we experimentally demonstrate that the proposed approach is feasible.

pi

DOI [BibTex]

DOI [BibTex]


Thumb xl publications toc
Magnetically actuated soft capsule endoscope for fine-needle aspiration biopsy

Son, D., Dogan, M. D., Sitti, M.

In Proceedings 2017 IEEE International Conference on Robotics and Automation (ICRA), pages: 1132-1139, IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (inproceedings)

Abstract
This paper presents a magnetically actuated soft capsule endoscope for fine-needle aspiration biopsy (B-MASCE) in the upper gastrointestinal tract. A thin and hollow needle is attached to the capsule, which can penetrate deeply into tissues to obtain subsurface biopsy sample. The design utilizes a soft elastomer body as a compliant mechanism to guide the needle. An internal permanent magnet provides a means for both actuation and tracking. The capsule is designed to roll towards its target and then deploy the biopsy needle in a precise location selected as the target area. B-MASCE is controlled by multiple custom-designed electromagnets while its position and orientation are tracked by a magnetic sensor array. In in vitro trials, B-MASCE demonstrated rolling locomotion and biopsy of a swine tissue model positioned inside an anatomical human stomach model. It was confirmed after the experiment that a tissue sample was retained inside the needle.

pi

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Thumb xl image toc
The use of clamping grips and friction pads by tree frogs for climbing curved surfaces

Endlein, T., Ji, A., Yuan, S., Hill, I., Wang, H., Barnes, W. J. P., Dai, Z., Sitti, M.

In Proc. R. Soc. B, 284(1849):20162867, Febuary 2017 (inproceedings)

Abstract
Most studies on the adhesive mechanisms of climbing animals have addressed attachment against flat surfaces, yet many animals can climb highly curved surfaces, like twigs and small branches. Here we investigated whether tree frogs use a clamping grip by recording the ground reaction forces on a cylindrical object with either a smooth or anti-adhesive, rough surface. Furthermore, we measured the contact area of fore and hindlimbs against differently sized transparent cylinders and the forces of individual pads and subarticular tubercles in restrained animals. Our study revealed that frogs use friction and normal forces of roughly a similar magnitude for holding on to cylindrical objects. When challenged with climbing a non-adhesive surface, the compressive forces between opposite legs nearly doubled, indicating a stronger clamping grip. In contrast to climbing flat surfaces, frogs increased the contact area on all limbs by engaging not just adhesive pads but also subarticular tubercles on curved surfaces. Our force measurements showed that tubercles can withstand larger shear stresses than pads. SEM images of tubercles revealed a similar structure to that of toe pads including the presence of nanopillars, though channels surrounding epithelial cells were less pronounced. The tubercles' smaller size, proximal location on the toes and shallow cells make them probably less prone to buckling and thus ideal for gripping curved surfaces.

pi

DOI [BibTex]

DOI [BibTex]


Thumb xl 9780262036436
Mobile Microrobotics

Sitti, M.

Mobile Microrobotics, The MIT Press, Cambridge, MA, 2017 (book)

Abstract
Progress in micro- and nano-scale science and technology has created a demand for new microsystems for high-impact applications in healthcare, biotechnology, manufacturing, and mobile sensor networks. The new robotics field of microrobotics has emerged to extend our interactions and explorations to sub-millimeter scales. This is the first textbook on micron-scale mobile robotics, introducing the fundamentals of design, analysis, fabrication, and control, and drawing on case studies of existing approaches. The book covers the scaling laws that can be used to determine the dominant forces and effects at the micron scale; models forces acting on microrobots, including surface forces, friction, and viscous drag; and describes such possible microfabrication techniques as photo-lithography, bulk micromachining, and deep reactive ion etching. It presents on-board and remote sensing methods, noting that remote sensors are currently more feasible; studies possible on-board microactuators; discusses self-propulsion methods that use self-generated local gradients and fields or biological cells in liquid environments; and describes remote microrobot actuation methods for use in limited spaces such as inside the human body. It covers possible on-board powering methods, indispensable in future medical and other applications; locomotion methods for robots on surfaces, in liquids, in air, and on fluid-air interfaces; and the challenges of microrobot localization and control, in particular multi-robot control methods for magnetic microrobots. Finally, the book addresses current and future applications, including noninvasive medical diagnosis and treatment, environmental remediation, and scientific tools.

pi

Mobile Microrobotics By Metin Sitti - Chapter 1 (PDF) link (url) [BibTex]

Mobile Microrobotics By Metin Sitti - Chapter 1 (PDF) link (url) [BibTex]


Thumb xl publications toc
Planning spin-walking locomotion for automatic grasping of microobjects by an untethered magnetic microgripper

Dong, X., Sitti, M.

In 2017 IEEE International Conference on Robotics and Automation (ICRA), pages: 6612-6618, 2017 (inproceedings)

Abstract
Most demonstrated mobile microrobot tasks so far have been achieved via pick-and-placing and dynamic trapping with teleoperation or simple path following algorithms. In our previous work, an untethered magnetic microgripper has been developed which has advanced functions, such as gripping objects. Both teleoperated manipulation in 2D and 3D have been demonstrated. However, it is challenging to control the magnetic microgripper to carry out manipulation tasks, because the grasping of objects so far in the literature relies heavily on teleoperation, which takes several minutes with even a skilled human expert. Here, we propose a new spin-walking locomotion and an automated 2D grasping motion planner for the microgripper, which enables time-efficient automatic grasping of microobjects that has not been achieved yet for untethered microrobots. In its locomotion, the microgripper repeatedly rotates about two principal axes to regulate its pose and move precisely on a surface. The motion planner could plan different motion primitives for grasping and compensate the uncertainties in the motion by learning the uncertainties and planning accordingly. We experimentally demonstrated that, using the proposed method, the microgripper could align to the target pose with error less than 0.1 body length and grip the objects within 40 seconds. Our method could significantly improve the time efficiency of micro-scale manipulation and have potential applications in microassembly and biomedical engineering.

pi

DOI Project Page [BibTex]

DOI Project Page [BibTex]

2012


Thumb xl screen shot 2015 08 23 at 13.56.29
Towards Multi-DOF model mediated teleoperation: Using vision to augment feedback

Willaert, B., Bohg, J., Van Brussel, H., Niemeyer, G.

In IEEE International Workshop on Haptic Audio Visual Environments and Games (HAVE), pages: 25-31, October 2012 (inproceedings)

Abstract
In this paper, we address some of the challenges that arise as model-mediated teleoperation is applied to systems with multiple degrees of freedom and multiple sensors. Specifically we use a system with position, force, and vision sensors to explore an environment geometry in two degrees of freedom. The inclusion of vision is proposed to alleviate the difficulties of estimating an increasing number of environment properties. Vision can furthermore increase the predictive nature of model-mediated teleoperation, by effectively predicting touch feedback before the slave is even in contact with the environment. We focus on the case of estimating the location and orientation of a local surface patch at the contact point between the slave and the environment. We describe the various information sources with their respective limitations and create a combined model estimator as part of a multi-d.o.f. model-mediated controller. An experiment demonstrates the feasibility and benefits of utilizing vision sensors in teleoperation.

am

DOI [BibTex]

2012


DOI [BibTex]


Thumb xl sankaran iros 20121
Failure Recovery with Shared Autonomy

Sankaran, B., Pitzer, B., Osentoski, S.

In International Conference on Intelligent Robots and Systems, October 2012 (inproceedings)

Abstract
Building robots capable of long term autonomy has been a long standing goal of robotics research. Such systems must be capable of performing certain tasks with a high degree of robustness and repeatability. In the context of personal robotics, these tasks could range anywhere from retrieving items from a refrigerator, loading a dishwasher, to setting up a dinner table. Given the complexity of tasks there are a multitude of failure scenarios that the robot can encounter, irrespective of whether the environment is static or dynamic. For a robot to be successful in such situations, it would need to know how to recover from failures or when to ask a human for help. This paper, presents a novel shared autonomy behavioral executive to addresses these issues. We demonstrate how this executive combines generalized logic based recovery and human intervention to achieve continuous failure free operation. We tested the systems over 250 trials of two different use case experiments. Our current algorithm drastically reduced human intervention from 26% to 4% on the first experiment and 46% to 9% on the second experiment. This system provides a new dimension to robot autonomy, where robots can exhibit long term failure free operation with minimal human supervision. We also discuss how the system can be generalized.

am

link (url) [BibTex]

link (url) [BibTex]


Thumb xl bottlehandovergrasp
Task-Based Grasp Adaptation on a Humanoid Robot

Bohg, J., Welke, K., León, B., Do, M., Song, D., Wohlkinger, W., Aldoma, A., Madry, M., Przybylski, M., Asfour, T., Marti, H., Kragic, D., Morales, A., Vincze, M.

In 10th IFAC Symposium on Robot Control, SyRoCo 2012, Dubrovnik, Croatia, September 5-7, 2012., pages: 779-786, September 2012 (inproceedings)

Abstract
In this paper, we present an approach towards autonomous grasping of objects according to their category and a given task. Recent advances in the field of object segmentation and categorization as well as task-based grasp inference have been leveraged by integrating them into one pipeline. This allows us to transfer task-specific grasp experience between objects of the same category. The effectiveness of the approach is demonstrated on the humanoid robot ARMAR-IIIa.

am

Video pdf DOI [BibTex]

Video pdf DOI [BibTex]


no image
Movement Segmentation and Recognition for Imitation Learning

Meier, F., Theodorou, E., Schaal, S.

In Seventeenth International Conference on Artificial Intelligence and Statistics, La Palma, Canary Islands, Fifteenth International Conference on Artificial Intelligence and Statistics , April 2012 (inproceedings)

am

link (url) [BibTex]

link (url) [BibTex]


no image
Inverse dynamics with optimal distribution of contact forces for the control of legged robots

Righetti, L., Schaal, S.

In Dynamic Walking 2012, Pensacola, 2012 (inproceedings)

am

[BibTex]

[BibTex]


no image
Topological optimization for continuum compliant mechanisms via morphological evolution of traditional mechanisms

Lum, GZ, Yeo, SH, Yang, GL, Teo, TJ, Sitti, M

In 4th International Conference on Computational Methods, pages: 8, 2012 (inproceedings)

pi

[BibTex]

[BibTex]


no image
Encoding of Periodic and their Transient Motions by a Single Dynamic Movement Primitive

Ernesti, J., Righetti, L., Do, M., Asfour, T., Schaal, S.

In 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012), pages: 57-64, IEEE, Osaka, Japan, November 2012 (inproceedings)

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Learning Force Control Policies for Compliant Robotic Manipulation

Kalakrishnan, M., Righetti, L., Pastor, P., Schaal, S.

In ICML’12 Proceedings of the 29th International Coference on International Conference on Machine Learning, pages: 49-50, Edinburgh, Scotland, 2012 (inproceedings)

am mg

[BibTex]

[BibTex]


no image
Flapping Wings with DC-Motors via Direct, Elastic Transmissions

Azhar, M., Campolo, D., Lau, G., Sitti, M.

In Proceedings of International Conference on Intelligent Unmanned Systems, 8, 2012 (inproceedings)

pi

[BibTex]

[BibTex]


no image
Investigation of bioinspired gecko fibers to improve adhesion of HeartLander surgical robot

Tortora, G., Glass, P., Wood, N., Aksak, B., Menciassi, A., Sitti, M., Riviere, C.

In Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE, pages: 908-911, 2012 (inproceedings)

pi

[BibTex]

[BibTex]


no image
Magnetic hysteresis for multi-state addressable magnetic microrobotic control

Diller, E., Miyashita, S., Sitti, M.

In Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on, pages: 2325-2331, 2012 (inproceedings)

pi

[BibTex]

[BibTex]


no image
Quadratic programming for inverse dynamics with optimal distribution of contact forces

Righetti, L., Schaal, S.

In 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012), pages: 538-543, IEEE, Osaka, Japan, November 2012 (inproceedings)

Abstract
In this contribution we propose an inverse dynamics controller for a humanoid robot that exploits torque redundancy to minimize any combination of linear and quadratic costs in the contact forces and the commands. In addition the controller satisfies linear equality and inequality constraints in the contact forces and the commands such as torque limits, unilateral contacts or friction cones limits. The originality of our approach resides in the formulation of the problem as a quadratic program where we only need to solve for the control commands and where the contact forces are optimized implicitly. Furthermore, we do not need a structured representation of the dynamics of the robot (i.e. an explicit computation of the inertia matrix). It is in contrast with existing methods based on quadratic programs. The controller is then robust to uncertainty in the estimation of the dynamics model and the optimization is fast enough to be implemented in high bandwidth torque control loops that are increasingly available on humanoid platforms. We demonstrate properties of our controller with simulations of a human size humanoid robot.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Towards Associative Skill Memories

Pastor, P., Kalakrishnan, M., Righetti, L., Schaal, S.

In 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012), pages: 309-315, IEEE, Osaka, Japan, November 2012 (inproceedings)

Abstract
Movement primitives as basis of movement planning and control have become a popular topic in recent years. The key idea of movement primitives is that a rather small set of stereotypical movements should suffice to create a large set of complex manipulation skills. An interesting side effect of stereotypical movement is that it also creates stereotypical sensory events, e.g., in terms of kinesthetic variables, haptic variables, or, if processed appropriately, visual variables. Thus, a movement primitive executed towards a particular object in the environment will associate a large number of sensory variables that are typical for this manipulation skill. These association can be used to increase robustness towards perturbations, and they also allow failure detection and switching towards other behaviors. We call such movement primitives augmented with sensory associations Associative Skill Memories (ASM). This paper addresses how ASMs can be acquired by imitation learning and how they can create robust manipulation skill by determining subsequent ASMs online to achieve a particular manipulation goal. Evaluation for grasping and manipulation with a Barrett WAM/Hand illustrate our approach.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Template-based learning of grasp selection

Herzog, A., Pastor, P., Kalakrishnan, M., Righetti, L., Asfour, T., Schaal, S.

In 2012 IEEE International Conference on Robotics and Automation, pages: 2379-2384, IEEE, Saint Paul, USA, 2012 (inproceedings)

Abstract
The ability to grasp unknown objects is an important skill for personal robots, which has been addressed by many present and past research projects, but still remains an open problem. A crucial aspect of grasping is choosing an appropriate grasp configuration, i.e. the 6d pose of the hand relative to the object and its finger configuration. Finding feasible grasp configurations for novel objects, however, is challenging because of the huge variety in shape and size of these objects. Moreover, possible configurations also depend on the specific kinematics of the robotic arm and hand in use. In this paper, we introduce a new grasp selection algorithm able to find object grasp poses based on previously demonstrated grasps. Assuming that objects with similar shapes can be grasped in a similar way, we associate to each demonstrated grasp a grasp template. The template is a local shape descriptor for a possible grasp pose and is constructed using 3d information from depth sensors. For each new object to grasp, the algorithm then finds the best grasp candidate in the library of templates. The grasp selection is also able to improve over time using the information of previous grasp attempts to adapt the ranking of the templates. We tested the algorithm on two different platforms, the Willow Garage PR2 and the Barrett WAM arm which have very different hands. Our results show that the algorithm is able to find good grasp configurations for a large set of objects from a relatively small set of demonstrations, and does indeed improve its performance over time.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Probabilistic depth image registration incorporating nonvisual information

Wüthrich, M., Pastor, P., Righetti, L., Billard, A., Schaal, S.

In 2012 IEEE International Conference on Robotics and Automation, pages: 3637-3644, IEEE, Saint Paul, USA, 2012 (inproceedings)

Abstract
In this paper, we derive a probabilistic registration algorithm for object modeling and tracking. In many robotics applications, such as manipulation tasks, nonvisual information about the movement of the object is available, which we will combine with the visual information. Furthermore we do not only consider observations of the object, but we also take space into account which has been observed to not be part of the object. Furthermore we are computing a posterior distribution over the relative alignment and not a point estimate as typically done in for example Iterative Closest Point (ICP). To our knowledge no existing algorithm meets these three conditions and we thus derive a novel registration algorithm in a Bayesian framework. Experimental results suggest that the proposed methods perform favorably in comparison to PCL [1] implementations of feature mapping and ICP, especially if nonvisual information is available.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]

1995


no image
A kendama learning robot based on a dynamic optimization theory

Miyamoto, H., Gandolfo, F., Gomi, H., Schaal, S., Koike, Y., Osu, R., Nakano, E., Kawato, M.

In Preceedings of the 4th IEEE International Workshop on Robot and Human Communication (RO-MAN’95), pages: 327-332, Tokyo, July 1995, clmc (inproceedings)

am

[BibTex]

1995


[BibTex]


no image
Visual tracking for moving multiple objects: an integration of vision and control

Sitti, M, Bozma, I, Denker, A

In Industrial Electronics, 1995. ISIE’95., Proceedings of the IEEE International Symposium on, 2, pages: 535-540, 1995 (inproceedings)

pi

[BibTex]

[BibTex]