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2015


Automatic LQR Tuning Based on Gaussian Process Optimization: Early Experimental Results
Automatic LQR Tuning Based on Gaussian Process Optimization: Early Experimental Results

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

Machine Learning in Planning and Control of Robot Motion Workshop at the IEEE/RSJ International Conference on Intelligent Robots and Systems (iROS), pages: , , Machine Learning in Planning and Control of Robot Motion Workshop, October 2015 (conference)

Abstract
This paper proposes an automatic controller tuning framework based on linear optimal control combined with Bayesian optimization. With this framework, an initial set of controller gains is automatically improved according to a pre-defined performance objective evaluated from experimental data. The underlying Bayesian optimization algorithm is Entropy Search, which represents the latent objective as a Gaussian process and constructs an explicit belief over the location of the objective minimum. This is used to maximize the information gain from each experimental evaluation. Thus, this framework shall yield improved controllers with fewer evaluations compared to alternative approaches. A seven-degree-of-freedom robot arm balancing an inverted pole is used as the experimental demonstrator. Preliminary results of a low-dimensional tuning problem highlight the method’s potential for automatic controller tuning on robotic platforms.

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PDF DOI Project Page [BibTex]

2015


PDF DOI Project Page [BibTex]


Direct Loss Minimization Inverse Optimal Control
Direct Loss Minimization Inverse Optimal Control

Doerr, A., Ratliff, N., Bohg, J., Toussaint, M., Schaal, S.

In Proceedings of Robotics: Science and Systems, Rome, Italy, Robotics: Science and Systems XI, July 2015 (inproceedings)

Abstract
Inverse Optimal Control (IOC) has strongly impacted the systems engineering process, enabling automated planner tuning through straightforward and intuitive demonstration. The most successful and established applications, though, have been in lower dimensional problems such as navigation planning where exact optimal planning or control is feasible. In higher dimensional systems, such as humanoid robots, research has made substantial progress toward generalizing the ideas to model free or locally optimal settings, but these systems are complicated to the point where demonstration itself can be difficult. Typically, real-world applications are restricted to at best noisy or even partial or incomplete demonstrations that prove cumbersome in existing frameworks. This work derives a very flexible method of IOC based on a form of Structured Prediction known as Direct Loss Minimization. The resulting algorithm is essentially Policy Search on a reward function that rewards similarity to demonstrated behavior (using Covariance Matrix Adaptation (CMA) in our experiments). Our framework blurs the distinction between IOC, other forms of Imitation Learning, and Reinforcement Learning, enabling us to derive simple, versatile, and practical algorithms that blend imitation and reinforcement signals into a unified framework. Our experiments analyze various aspects of its performance and demonstrate its efficacy on conveying preferences for motion shaping and combined reach and grasp quality optimization.

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PDF Video Project Page [BibTex]

PDF Video Project Page [BibTex]


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LMI-Based Synthesis for Distributed Event-Based State Estimation

Muehlebach, M., Trimpe, S.

In Proceedings of the American Control Conference, July 2015 (inproceedings)

Abstract
This paper presents an LMI-based synthesis procedure for distributed event-based state estimation. Multiple agents observe and control a dynamic process by sporadically exchanging data over a broadcast network according to an event-based protocol. In previous work [1], the synthesis of event-based state estimators is based on a centralized design. In that case three different types of communication are required: event-based communication of measurements, periodic reset of all estimates to their joint average, and communication of inputs. The proposed synthesis problem eliminates the communication of inputs as well as the periodic resets (under favorable circumstances) by accounting explicitly for the distributed structure of the control system.

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PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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Guaranteed H2 Performance in Distributed Event-Based State Estimation

Muehlebach, M., Trimpe, S.

In Proceeding of the First International Conference on Event-based Control, Communication, and Signal Processing, June 2015 (inproceedings)

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PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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On the Choice of the Event Trigger in Event-based Estimation

Trimpe, S., Campi, M.

In Proceeding of the First International Conference on Event-based Control, Communication, and Signal Processing, June 2015 (inproceedings)

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PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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Event-based Estimation and Control for Remote Robot Operation with Reduced Communication

Trimpe, S., Buchli, J.

In Proceedings of the IEEE International Conference on Robotics and Automation, May 2015 (inproceedings)

Abstract
An event-based communication framework for remote operation of a robot via a bandwidth-limited network is proposed. The robot sends state and environment estimation data to the operator, and the operator transmits updated control commands or policies to the robot. Event-based communication protocols are designed to ensure that data is transmitted only when required: the robot sends new estimation data only if this yields a significant information gain at the operator, and the operator transmits an updated control policy only if this comes with a significant improvement in control performance. The developed framework is modular and can be used with any standard estimation and control algorithms. Simulation results of a robotic arm highlight its potential for an efficient use of limited communication resources, for example, in disaster response scenarios such as the DARPA Robotics Challenge.

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PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


Comparing the effect of different spine and leg designs for a small bounding quadruped robot
Comparing the effect of different spine and leg designs for a small bounding quadruped robot

Eckert, P., Spröwitz, A., Witte, H., Ijspeert, A. J.

In Proceedings of ICRA, pages: 3128-3133, Seattle, Washington, USA, 2015 (inproceedings)

Abstract
We present Lynx-robot, a quadruped, modular, compliant machine. It alternately features a directly actuated, single-joint spine design, or an actively supported, passive compliant, multi-joint spine configuration. Both spine con- figurations bend in the sagittal plane. This study aims at characterizing these two, largely different spine concepts, for a bounding gait of a robot with a three segmented, pantograph leg design. An earlier, similar-sized, bounding, quadruped robot named Bobcat with a two-segment leg design and a directly actuated, single-joint spine design serves as a comparison robot, to study and compare the effect of the leg design on speed, while keeping the spine design fixed. Both proposed spine designs (single rotatory and active and multi-joint compliant) reach moderate, self-stable speeds.

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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A New Perspective and Extension of the Gaussian Filter

Wüthrich, M., Trimpe, S., Kappler, D., Schaal, S.

In Robotics: Science and Systems, 2015 (inproceedings)

Abstract
The Gaussian Filter (GF) is one of the most widely used filtering algorithms; instances are the Extended Kalman Filter, the Unscented Kalman Filter and the Divided Difference Filter. GFs represent the belief of the current state by a Gaussian with the mean being an affine function of the measurement. We show that this representation can be too restrictive to accurately capture the dependencies in systems with nonlinear observation models, and we investigate how the GF can be generalized to alleviate this problem. To this end we view the GF from a variational-inference perspective, and analyze how restrictions on the form of the belief can be relaxed while maintaining simplicity and efficiency. This analysis provides a basis for generalizations of the GF. We propose one such generalization which coincides with a GF using a virtual measurement, obtained by applying a nonlinear function to the actual measurement. Numerical experiments show that the proposed Feature Gaussian Filter (FGF) can have a substantial performance advantage over the standard GF for systems with nonlinear observation models.

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Web PDF Project Page [BibTex]

2008


Passive compliant quadruped robot using central pattern generators for locomotion control
Passive compliant quadruped robot using central pattern generators for locomotion control

Rutishauser, S., Spröwitz, A., Righetti, L., Ijspeert, A. J.

In Proceedings of the 2008 2nd Biennial IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, pages: 710-715, IEEE, Scottsdale, AZ, 2008 (inproceedings)

Abstract
We present a new quadruped robot, “Cheetah”, featuring three-segment pantographic legs with passive compliant knee joints. Each leg has two degrees of freedom - knee and hip joint can be actuated using proximal mounted RC servo motors, force transmission to the knee is achieved by means of a Bowden cable mechanism. Simple electronics to command the actuators from a desktop computer have been designed in order to test the robot. A Central Pattern Generator (CPG) network has been implemented to generate different gaits. A parameter space search was performed and tested on the robot to optimize forward velocity.

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DOI [BibTex]

2008


DOI [BibTex]


Graph signature for self-reconfiguration planning
Graph signature for self-reconfiguration planning

Asadpour, M., Spröwitz, A., Billard, A., Dillenbourg, P., Ijspeert, A. J.

In Proceedings of the 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 863-869, IEEE, Nice, 2008 (inproceedings)

Abstract
This project incorporates modular robots as build- ing blocks for furniture that moves and self-reconfigures. The reconfiguration is done using dynamic connection / disconnection of modules and rotations of the degrees of freedom. This paper introduces a new approach to self-reconfiguration planning for modular robots based on the graph signature and the graph edit-distance. The method has been tested in simulation on two type of modules: YaMoR and M-TRAN. The simulation results shows interesting features of the approach, namely rapidly finding a near-optimal solution.

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DOI [BibTex]

DOI [BibTex]


An active connection mechanism for modular self-reconfigurable robotic systems based on physical latching
An active connection mechanism for modular self-reconfigurable robotic systems based on physical latching

Spröwitz, A., Asadpour, M., Bourquin, Y., Ijspeert, A. J.

In Proceedings on the 2008 IEEE International Conference on Robotics and Automation (ICRA), 2008, pages: 3508-3513, IEEE, Pasadena, CA, 2008 (inproceedings)

Abstract
This article presents a robust and heavy duty physical latching connection mechanism, which can be actuated with DC motors to actively connect and disconnect modular robot units. The special requirements include a lightweight and simple construction providing an active, strong, hermaphrodite, completely retractable connection mechanism with a 90 degree symmetry and a no-energy consumption in the locked state. The mechanism volume is kept small to fit multiple copies into a single modular robot unit and to be used on as many faces of the robot unit as possible. This way several different lattice like modular robot structures are possible. The large selection for dock-able connection positions will likely simplify self-reconfiguration strategies. Tests with the implemented mechanism demonstrate its applicative potential for self-reconfiguring modular robots.

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DOI [BibTex]

DOI [BibTex]