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Authors: Bellicoso, C. D.; Bjelonic, M.; Wellhausen, L.; Holtmann, K.; Günther, F.; Tranzatto, M.; Fankhauser, P.; Hutter, M.
- Published in: Journal of Field Robotics (Volume: 35, Issue: 8)
- DOI: 10.3929/ethz-b-000294689
- Date: October 2019
This paper introduces a method to simultaneously optimize design and control parameters for legged robots to improve the performance of locomotion based tasks. The morphology of a quadrupedal robot was optimized for a trotting and bounding gait to achieve a certain speed while tuning the control parameters of a robust locomotion controller at the same time. The results of the optimization show that a change of the structure of the robot can help increase its admissable top speed while using the same actuation units.
This paper presents the application of operational space control based on hierarchical task optimization for quadrupedal locomotion. We show how the behavior of a complex robotic machine can be described by a simple set of least squares problems with different priorities for motion, torque, and force optimization. Using projected dynamics of floating base systems with multiple contact points, the optimization dimensionality can be reduced or decoupled such that the formulation is purely based on the inversion of kinematic system properties. The present controller is extensively tested in various experiments using the fully torque controllable quadrupedal robot StarlETH. The load distribution is optimized for static walking gaits to improve contact stability and/or actuator efficiency under various terrain conditions. This is augmented with simultaneous joint position and torque limitations as well as with an interpolation method to ensure smooth contact transitions. The same control structure is further used to stabilize dynamic trotting gaits under significant external disturbances such as uneven ground or pushes. To the best of our knowledge, this work is the first documentation of static and dynamic locomotion with pure task-space inverse dynamics (no joint position feedback) control.
Authors: Suzano Medeiros,V.; Jelavic, E.; Bjelonic, M.; Siegwart, R.; Meggiolaro, M. A.; Hutter, M.
Wheeled-legged robots are an attractive solution for versatile locomotion in challenging terrain. They combine the speed and efficiency of wheels with the ability of legs to traverse challenging terrain. In this paper, we present a trajectory optimization formulation for wheeled-legged robots that optimizes over the base and wheels’ positions and forces and takes into account the terrain information while computing the plans. This enables us to find optimal driving motions over challenging terrain. The robot is modeled as a single rigid-body, which allows us to plan complex motions and still keep a low computational complexity to solve the optimization quickly. The terrain map, together with the use of a stability constraint, allows the optimizer to generate feasible motions that cannot be discovered without taking the terrain information into account. The optimization is formulated as a Nonlinear Programming (NLP) problem and the reference motions are tracked by a hierarchical whole-body controller that computes the torque actuation commands for the robot. The trajectories have been experimentally verified on quadrupedal robot ANYmal equipped with non-steerable torque-controlled wheels. Our trajectory optimization framework enables wheeled quadrupedal robots to drive over challenging terrain, e.g., steps, slopes, stairs, while negotiating these obstacles with dynamic motions.
- Published in: EEE Robotics and Automation Letters
- Detailed record: yy
- DOI: 10.1109/LRA.2020.2990720
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- Date: 2020