Combined Sampling and Optimization Based Planning for Legged-Wheeled Robots (ICRA 2021 Presentation)

Описание: Presentation for the IEEE International Conference on Robotics and Automation (ICRA) 2021

Paper available here: https://arxiv.org/abs/2104.04247

Abstract— Planning for legged-wheeled machines is typically done using trajectory optimization because of many degrees of freedom, thus rendering legged-wheeled planners prone to falling prey to bad local minima. We present a combined sampling and optimization-based planning approach that can cope with challenging terrain. The sampling-based stage computes whole-body configurations and contact schedule, which speeds up the optimization convergence. The optimization-based stage ensures that all the system constraints, such as non-holonomic rolling constraints, are satisfied. The evaluations show the importance of good initial guesses for optimization. Furthermore, they suggest that terrain/collision (avoidance) constraints are more challenging than the robot model’s constraints. Lastly, we extend the optimization to handle general terrain representations in the form of elevation maps.

Authors: Edo Jelavic, Farbod Farshidian, and Marco Hutter

This research was supported by the Swiss National Science Foundation (SNSF) as part of project No.188596, by the European Research Council(ERC) under the European Union’s Horizon 2020 research and innovation programme grant agreement No 852044 and through the SNSF National Centre of Competence in Digital Fabrication (NCCR dfab).