Publications

DEPARTMENTS

Emperical Interference

Haptic Intelligence

Modern Magnetic Systems

Perceiving Systems

Physical Intelligence

Robotic Materials

Social Foundations of Computation


Research Groups

Autonomous Vision

Autonomous Learning

Bioinspired Autonomous Miniature Robots

Dynamic Locomotion

Embodied Vision

Human Aspects of Machine Learning

Intelligent Control Systems

Learning and Dynamical Systems

Locomotion in Biorobotic and Somatic Systems

Micro, Nano, and Molecular Systems

Movement Generation and Control

Neural Capture and Synthesis

Physics for Inference and Optimization

Organizational Leadership and Diversity

Probabilistic Learning Group


Topics

Robot Learning

Conference Paper

2022

Autonomous Learning

Robotics

AI

Career

Award


Movement Generation and Control Book Chapter Momentum-Centered Control of Contact Interactions Righetti, L., Herzog, A. In Geometric and Numerical Foundations of Movements, 117:339-359, Springer Tracts in Advanced Robotics, Springer, Cham, 2017 URL BibTeX

Movement Generation and Control Autonomous Motion Book Chapter Using Torque Redundancy to Optimize Contact Forces in Legged Robots Righetti, L., Buchli, J., Mistry, M., Kalakrishnan, M., Schaal, S. In Redundancy in Robot Manipulators and Multi-Robot Systems, 57:35-51, Lecture Notes in Electrical Engineering, Springer Berlin Heidelberg, 2013
The development of legged robots for complex environments requires controllers that guarantee both high tracking performance and compliance with the environment. More specifically the control of contact interaction with the environment is of crucial importance to ensure stable, robust and safe motions. In the following, we present an inverse dynamics controller that exploits torque redundancy to directly and explicitly minimize any combination of linear and quadratic costs in the contact constraints and in the commands. Such a result is particularly relevant for legged robots as it allows to use torque redundancy to directly optimize contact interactions. For example, given a desired locomotion behavior, it can guarantee the minimization of contact forces to reduce slipping on difficult terrains while ensuring high tracking performance of the desired motion. The proposed controller is very simple and computationally efficient, and most importantly it can greatly improve the performance of legged locomotion on difficult terrains as can be seen in the experimental results.
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