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16 results (View BibTeX file of all listed publications)

2016

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Predictive and Self Triggering for Event-based State Estimation

Trimpe, S.

In Proceedings of the 55th IEEE Conference on Decision and Control (CDC), pages: 3098-3105, Las Vegas, NV, USA, December 2016 (inproceedings)

am ics

arXiv PDF DOI Project Page [BibTex]

2016

am ics Trimpe, S. Predictive and Self Triggering for Event-based State Estimation In Proceedings of the 55th IEEE Conference on Decision and Control (CDC), pages: 3098-3105, Las Vegas, NV, USA, December 2016 (inproceedings)

arXiv PDF DOI Project Page [BibTex]

Thumb xl screen shot 2015 12 04 at 15.11.43
Robust Gaussian Filtering using a Pseudo Measurement

Wüthrich, M., Garcia Cifuentes, C., Trimpe, S., Meier, F., Bohg, J., Issac, J., Schaal, S.

In Proceedings of the American Control Conference (ACC), Boston, MA, USA, July 2016 (inproceedings)

Abstract
Most widely-used state estimation algorithms, such as the Extended Kalman Filter and the Unscented Kalman Filter, belong to the family of Gaussian Filters (GF). Unfortunately, GFs fail if the measurement process is modelled by a fat-tailed distribution. This is a severe limitation, because thin-tailed measurement models, such as the analytically-convenient and therefore widely-used Gaussian distribution, are sensitive to outliers. In this paper, we show that mapping the measurements into a specific feature space enables any existing GF algorithm to work with fat-tailed measurement models. We find a feature function which is optimal under certain conditions. Simulation results show that the proposed method allows for robust filtering in both linear and nonlinear systems with measurements contaminated by fat-tailed noise.

am ics

Web link (url) DOI Project Page [BibTex]

am ics Wüthrich, M., Garcia Cifuentes, C., Trimpe, S., Meier, F., Bohg, J., Issac, J., Schaal, S. Robust Gaussian Filtering using a Pseudo Measurement In Proceedings of the American Control Conference (ACC), Boston, MA, USA, July 2016 (inproceedings)

Web link (url) DOI Project Page [BibTex]

Thumb xl screen shot 2016 01 19 at 14.48.37
Automatic LQR Tuning Based on Gaussian Process Global Optimization

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

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 270-277, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (inproceedings)

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. Results of a two- and four- dimensional tuning problems highlight the method’s potential for automatic controller tuning on robotic platforms.

am ics pn

Video PDF DOI Project Page [BibTex]

am ics pn Marco, A., Hennig, P., Bohg, J., Schaal, S., Trimpe, S. Automatic LQR Tuning Based on Gaussian Process Global Optimization In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 270-277, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (inproceedings)

Video PDF DOI Project Page [BibTex]

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Depth-based Object Tracking Using a Robust Gaussian Filter

Issac, J., Wüthrich, M., Garcia Cifuentes, C., Bohg, J., Trimpe, S., Schaal, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2016, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (inproceedings)

Abstract
We consider the problem of model-based 3D- tracking of objects given dense depth images as input. Two difficulties preclude the application of a standard Gaussian filter to this problem. First of all, depth sensors are characterized by fat-tailed measurement noise. To address this issue, we show how a recently published robustification method for Gaussian filters can be applied to the problem at hand. Thereby, we avoid using heuristic outlier detection methods that simply reject measurements if they do not match the model. Secondly, the computational cost of the standard Gaussian filter is prohibitive due to the high-dimensional measurement, i.e. the depth image. To address this problem, we propose an approximation to reduce the computational complexity of the filter. In quantitative experiments on real data we show how our method clearly outperforms the standard Gaussian filter. Furthermore, we compare its performance to a particle-filter-based tracking method, and observe comparable computational efficiency and improved accuracy and smoothness of the estimates.

am ics

Video Bayesian Object Tracking Library Bayesian Filtering Framework Object Tracking Dataset link (url) DOI Project Page [BibTex]

am ics Issac, J., Wüthrich, M., Garcia Cifuentes, C., Bohg, J., Trimpe, S., Schaal, S. Depth-based Object Tracking Using a Robust Gaussian Filter In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2016, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (inproceedings)

Video Bayesian Object Tracking Library Bayesian Filtering Framework Object Tracking Dataset link (url) DOI Project Page [BibTex]

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Communication Rate Analysis for Event-based State Estimation

(Best student paper finalist)

Ebner, S., Trimpe, S.

In Proceedings of the 13th International Workshop on Discrete Event Systems, May 2016 (inproceedings)

am ics

PDF DOI [BibTex]

am ics Ebner, S., Trimpe, S. Communication Rate Analysis for Event-based State Estimation In Proceedings of the 13th International Workshop on Discrete Event Systems, May 2016 (inproceedings)

PDF DOI [BibTex]

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Supplemental material for ’Communication Rate Analysis for Event-based State Estimation’

Ebner, S., Trimpe, S.

Max Planck Institute for Intelligent Systems, January 2016 (techreport)

am ics

PDF [BibTex]

am ics Ebner, S., Trimpe, S. Supplemental material for ’Communication Rate Analysis for Event-based State Estimation’ Max Planck Institute for Intelligent Systems, January 2016 (techreport)

PDF [BibTex]

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A Convex Model of Momentum Dynamics for Multi-Contact Motion Generation

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

In 2016 IEEE-RAS 16th International Conference on Humanoid Robots Humanoids, pages: 842-849, IEEE, Cancun, Mexico, 2016 (inproceedings)

Abstract
Linear models for control and motion generation of humanoid robots have received significant attention in the past years, not only due to their well known theoretical guarantees, but also because of practical computational advantages. However, to tackle more challenging tasks and scenarios such as locomotion on uneven terrain, a more expressive model is required. In this paper, we are interested in contact interaction-centered motion optimization based on the momentum dynamics model. This model is non-linear and non-convex; however, we find a relaxation of the problem that allows us to formulate it as a single convex quadratically-constrained quadratic program (QCQP) that can be very efficiently optimized and is useful for multi-contact planning. This convex model is then coupled to the optimization of end-effector contact locations using a mixed integer program, which can also be efficiently solved. This becomes relevant e.g. to recover from external pushes, where a predefined stepping plan is likely to fail and an online adaptation of the contact location is needed. The performance of our algorithm is demonstrated in several multi-contact scenarios for a humanoid robot.

am mg

link (url) DOI [BibTex]

am mg Ponton, B., Herzog, A., Schaal, S., Righetti, L. A Convex Model of Momentum Dynamics for Multi-Contact Motion Generation In 2016 IEEE-RAS 16th International Conference on Humanoid Robots Humanoids, pages: 842-849, IEEE, Cancun, Mexico, 2016 (inproceedings)

link (url) DOI [BibTex]

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On the Effects of Measurement Uncertainty in Optimal Control of Contact Interactions

Ponton, B., Schaal, S., Righetti, L.

In The 12th International Workshop on the Algorithmic Foundations of Robotics WAFR, Berkeley, USA, 2016 (inproceedings)

Abstract
Stochastic Optimal Control (SOC) typically considers noise only in the process model, i.e. unknown disturbances. However, in many robotic applications involving interaction with the environment, such as locomotion and manipulation, uncertainty also comes from lack of precise knowledge of the world, which is not an actual disturbance. We analyze the effects of also considering noise in the measurement model, by devel- oping a SOC algorithm based on risk-sensitive control, that includes the dynamics of an observer in such a way that the control law explicitly de- pends on the current measurement uncertainty. In simulation results on a simple 2D manipulator, we have observed that measurement uncertainty leads to low impedance behaviors, a result in contrast with the effects of process noise that creates stiff behaviors. This suggests that taking into account measurement uncertainty could be a potentially very interesting way to approach problems involving uncertain contact interactions.

am mg

link (url) [BibTex]

am mg Ponton, B., Schaal, S., Righetti, L. On the Effects of Measurement Uncertainty in Optimal Control of Contact Interactions In The 12th International Workshop on the Algorithmic Foundations of Robotics WAFR, Berkeley, USA, 2016 (inproceedings)

link (url) [BibTex]

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Inertial Sensor-Based Humanoid Joint State Estimation

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

In 2016 IEEE International Conference on Robotics and Automation (ICRA), pages: 1825-1831, IEEE, Stockholm, Sweden, 2016 (inproceedings)

Abstract
This work presents methods for the determination of a humanoid robot's joint velocities and accelerations directly from link-mounted Inertial Measurement Units (IMUs) each containing a three-axis gyroscope and a three-axis accelerometer. No information about the global pose of the floating base or its links is required and precise knowledge of the link IMU poses is not necessary due to presented calibration routines. Additionally, a filter is introduced to fuse gyroscope angular velocities with joint position measurements and compensate the computed joint velocities for time-varying gyroscope biases. The resulting joint velocities are subject to less noise and delay than filtered velocities computed from numerical differentiation of joint potentiometer signals, leading to superior performance in joint feedback control as demonstrated in experiments performed on a SARCOS hydraulic humanoid.

am mg

link (url) DOI [BibTex]

am mg Rotella, N., Mason, S., Schaal, S., Righetti, L. Inertial Sensor-Based Humanoid Joint State Estimation In 2016 IEEE International Conference on Robotics and Automation (ICRA), pages: 1825-1831, IEEE, Stockholm, Sweden, 2016 (inproceedings)

link (url) DOI [BibTex]

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Stepping Stabilization Using a Combination of DCM Tracking and Step Adjustment

Khadiv, M., Kleff, S., Herzog, A., Moosavian, S. A. A., Schaal, S., Righetti, L.

In 2016 4th International Conference on Robotics and Mechatronics (ICROM), pages: 130-135, IEEE, Teheran, Iran, 2016 (inproceedings)

Abstract
In this paper, a method for stabilizing biped robots stepping by a combination of Divergent Component of Motion (DCM) tracking and step adjustment is proposed. In this method, the DCM trajectory is generated, consistent with the predefined footprints. Furthermore, a swing foot trajectory modification strategy is proposed to adapt the landing point, using DCM measurement. In order to apply the generated trajectories to the full robot, a Hierarchical Inverse Dynamics (HID) is employed. The HID enables us to use different combinations of the DCM tracking and step adjustment for stabilizing different biped robots. Simulation experiments on two scenarios for two different simulated robots, one with active ankles and the other with passive ankles, are carried out. Simulation results demonstrate the effectiveness of the proposed method for robots with both active and passive ankles.

am mg

link (url) DOI [BibTex]

am mg Khadiv, M., Kleff, S., Herzog, A., Moosavian, S. A. A., Schaal, S., Righetti, L. Stepping Stabilization Using a Combination of DCM Tracking and Step Adjustment In 2016 4th International Conference on Robotics and Mechatronics (ICROM), pages: 130-135, IEEE, Teheran, Iran, 2016 (inproceedings)

link (url) DOI [BibTex]

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Structured contact force optimization for kino-dynamic motion generation

Herzog, A., Schaal, S., Righetti, L.

In 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 2703-2710, IEEE, Daejeon, South Korea, 2016 (inproceedings)

Abstract
Optimal control approaches in combination with trajectory optimization have recently proven to be a promising control strategy for legged robots. Computationally efficient and robust algorithms were derived using simplified models of the contact interaction between robot and environment such as the linear inverted pendulum model (LIPM). However, as humanoid robots enter more complex environments, less restrictive models become increasingly important. As we leave the regime of linear models, we need to build dedicated solvers that can compute interaction forces together with consistent kinematic plans for the whole-body. In this paper, we address the problem of planning robot motion and interaction forces for legged robots given predefined contact surfaces. The motion generation process is decomposed into two alternating parts computing force and motion plans in coherence. We focus on the properties of the momentum computation leading to sparse optimal control formulations to be exploited by a dedicated solver. In our experiments, we demonstrate that our motion generation algorithm computes consistent contact forces and joint trajectories for our humanoid robot. We also demonstrate the favorable time complexity due to our formulation and composition of the momentum equations.

am mg

link (url) DOI [BibTex]

am mg Herzog, A., Schaal, S., Righetti, L. Structured contact force optimization for kino-dynamic motion generation In 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 2703-2710, IEEE, Daejeon, South Korea, 2016 (inproceedings)

link (url) DOI [BibTex]

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Balancing and Walking Using Full Dynamics LQR Control With Contact Constraints

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

In 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), pages: 63-68, IEEE, Cancun, Mexico, 2016 (inproceedings)

Abstract
Torque control algorithms which consider robot dynamics and contact constraints are important for creating dynamic behaviors for humanoids. As computational power increases, algorithms tend to also increase in complexity. However, it is not clear how much complexity is really required to create controllers which exhibit good performance. In this paper, we study the capabilities of a simple approach based on contact consistent LQR controllers designed around key poses to control various tasks on a humanoid robot. We present extensive experimental results on a hydraulic, torque controlled humanoid performing balancing and stepping tasks. This feedback control approach captures the necessary synergies between the DoFs of the robot to guarantee good control performance. We show that for the considered tasks, it is only necessary to re-linearize the dynamics of the robot at different contact configurations and that increasing the number of LQR controllers along desired trajectories does not improve performance. Our result suggest that very simple controllers can yield good performance competitive with current state of the art, but more complex, optimization-based whole-body controllers. A video of the experiments can be found at https://youtu.be/5T08CNKV1hw.

am mg

link (url) DOI [BibTex]

am mg Mason, S., Rotella, N., Schaal, S., Righetti, L. Balancing and Walking Using Full Dynamics LQR Control With Contact Constraints In 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), pages: 63-68, IEEE, Cancun, Mexico, 2016 (inproceedings)

link (url) DOI [BibTex]

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Step Timing Adjustement: a Step toward Generating Robust Gaits

Khadiv, M., Herzog, A., Moosavian, S. A. A., Righetti, L.

In 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), pages: 35-42, IEEE, Cancun, Mexico, 2016 (inproceedings)

Abstract
Step adjustment for humanoid robots has been shown to improve robustness in gaits. However, step duration adaptation is often neglected in control strategies. In this paper, we propose an approach that combines both step location and timing adjustment for generating robust gaits. In this approach, step location and step timing are decided, based on feedback from the current state of the robot. The proposed approach is comprised of two stages. In the first stage, the nominal step location and step duration for the next step or a previewed number of steps are specified. In this stage which is done at the start of each step, the main goal is to specify the best step length and step duration for a desired walking speed. The second stage deals with finding the best landing point and landing time of the swing foot at each control cycle. In this stage, stability of the gaits is preserved by specifying a desired offset between the swing foot landing point and the Divergent Component of Motion (DCM) at the end of current step. After specifying the landing point of the swing foot at a desired time, the swing foot trajectory is regenerated at each control cycle to realize desired landing properties. Simulation on different scenarios shows the robustness of the generated gaits from our proposed approach compared to the case where no timing adjustment is employed.

mg

link (url) DOI [BibTex]

mg Khadiv, M., Herzog, A., Moosavian, S. A. A., Righetti, L. Step Timing Adjustement: a Step toward Generating Robust Gaits In 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), pages: 35-42, IEEE, Cancun, Mexico, 2016 (inproceedings)

link (url) DOI [BibTex]

2007

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Hand placement during quadruped locomotion in a humanoid robot: A dynamical system approach

Degallier, S., Righetti, L., Ijspeert, A.

In 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 2047-2052, IEEE, San Diego, USA, 2007 (inproceedings)

Abstract
Locomotion on an irregular surface is a challenging task in robotics. Among different problems to solve to obtain robust locomotion, visually guided locomotion and accurate foot placement are of crucial importance. Robust controllers able to adapt to sensory-motor feedbacks, in particular to properly place feet on specific locations, are thus needed. Dynamical systems are well suited for this task as any online modification of the parameters leads to a smooth adaptation of the trajectories, allowing a safe integration of sensory-motor feedback. In this contribution, as a first step in the direction of locomotion on irregular surfaces, we present a controller that allows hand placement during crawling in a simulated humanoid robot. The goal of the controller is to superimpose rhythmic movements for crawling with discrete (i.e. short-term) modulations of the hand placements to reach specific marks on the ground.

mg

link (url) DOI [BibTex]

2007

mg Degallier, S., Righetti, L., Ijspeert, A. Hand placement during quadruped locomotion in a humanoid robot: A dynamical system approach In 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 2047-2052, IEEE, San Diego, USA, 2007 (inproceedings)

link (url) DOI [BibTex]

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Lower body realization of the baby humanoid - ‘iCub’

Tsagarakis, N., Becchi, F., Righetti, L., Ijspeert, A., Caldwell, D.

In 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 3616-3622, IEEE, San Diego, USA, 2007 (inproceedings)

Abstract
Nowadays, the understanding of the human cognition and it application to robotic systems forms a great challenge of research. The iCub is a robotic platform that was developed within the RobotCub European project to provide the cognition research community with an open baby- humanoid platform for understanding and development of cognitive systems. In this paper we present the design requirements and mechanical realization of the lower body developed for the "iCub". In particular the leg and the waist mechanisms adopted for lower body to match the size and physical abilities of a 2 frac12 year old human baby are introduced.

mg

link (url) DOI [BibTex]

mg Tsagarakis, N., Becchi, F., Righetti, L., Ijspeert, A., Caldwell, D. Lower body realization of the baby humanoid - ‘iCub’ In 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 3616-3622, IEEE, San Diego, USA, 2007 (inproceedings)

link (url) DOI [BibTex]

2004

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Operating system support for interface virtualisation of reconfigurable coprocessors

Vuletic, M., Righetti, L., Pozzi, L., Ienne, P.

In In Proceedings of the Design, Automation and Test in Europe Conference and Exhibition, pages: 748-749, IEEE, Paris, France, 2004 (inproceedings)

Abstract
Reconfigurable systems-on-chip (SoC) consist of large field programmable gate arrays (FPGAs) and standard processors. The reconfigurable logic can be used for application-specific coprocessors to speedup execution of applications. The widespread use is limited by the complexity of interfacing software applications with coprocessors. We present a virtualization layer that lowers the interfacing complexity and improves the portability. The layer shifts the burden of moving data between processor and coprocessor from the programmer to the operating system (OS). A reconfigurable SoC running Linux is used to prove the concept.

mg

link (url) DOI [BibTex]

2004

mg Vuletic, M., Righetti, L., Pozzi, L., Ienne, P. Operating system support for interface virtualisation of reconfigurable coprocessors In In Proceedings of the Design, Automation and Test in Europe Conference and Exhibition, pages: 748-749, IEEE, Paris, France, 2004 (inproceedings)

link (url) DOI [BibTex]