Whole‐body motion planning and control of a quadruped robot for challenging terrain
Authors:
- 23 May 2023
- journal article
- research article
- Published by Wiley in Journal of Field Robotics
- Vol. 40 (6) , 1657-1677
Abstract
Quadruped robots working in jungles, mountains or factories should be able to move through challenging scenarios. In this paper, we present a control framework for quadruped robots walking over rough terrain. The planner plans the trajectory of the robot's center of gravity by using the normalized energy stability criterion, which ensures that the robot is in the most stable state. A contact detection algorithm based on the probabilistic contact model is presented, which implements event‐based state switching of the quadruped robot legs. And an on‐line detection of contact force based on generalized momentum is also showed, which improves the accuracy of proprioceptive force estimation. A controller combining whole body control and virtual model control is proposed to achieve precise trajectory tracking and active compliance with environment interaction. Without any knowledge of the environment, the experiments of the quadruped robot SDUQuad‐144 climbs over significant obstacles such as 38 cm high steps and 22.5 cm high stairs are designed to verify the feasibility of the proposed method.Keywords
This publication has 36 references indexed in Scilit:
- ANYmal - toward legged robots for harsh environmentsAdvanced Robotics, 2017
- Probabilistic foot contact estimation by fusing information from dynamics and differential/forward kinematics2016
- ANYmal - a highly mobile and dynamic quadrupedal robot2016
- High-slope terrain locomotion for torque-controlled quadruped robotsAutonomous Robots, 2016
- Planning and execution of dynamic whole-body locomotion for a hydraulic quadruped on challenging terrain2015
- An overview of null space projections for redundant, torque-controlled robotsThe International Journal of Robotics Research, 2015
- Path planning with force-based foothold adaptation and virtual model control for torque controlled quadruped robots2014
- Optimization and learning for rough terrain legged locomotionThe International Journal of Robotics Research, 2011
- Comprehensive summary of the Institute for Human and Machine Cognition’s experience with LittleDogThe International Journal of Robotics Research, 2011
- Learning, planning, and control for quadruped locomotion over challenging terrainThe International Journal of Robotics Research, 2010