Quadruped robot trotting over irregular terrain assisted by stereo-vision

• Published in: Intelligent service robotics Vol. 7; no. 2; pp. 67 - 77
• Main Authors: Bazeille, Stéphane, Barasuol, Victor, Focchi, Michele, Havoutis, Ioannis, Frigerio, Marco, Buchli, Jonas, Caldwell, Darwin G., Semini, Claudio
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2014; Springer Nature B.V
• Subjects: Artificial Intelligence; Autonomous navigation; Barriers; Cameras; Closed loops; Cognition & reasoning; Control; Control algorithms; Controllers; Dynamical Systems; Engineering; Feedback; Ground plane; Localization; Locomotion; Mapping; Mechatronics; Planning; Robot dynamics; Robotics; Robotics and Automation; Robots; Rough terrain; Sensors; Special Issue; Trajectory control; User Interfaces and Human Computer Interaction; Vibration; Vision; Vision systems; Reactive walking; Goal-oriented navigation; Visual servoing; Quadruped robot; Active impedance
• ISSN: 1861-2776; 1861-2784
• DOI: 10.1007/s11370-014-0147-9

Legged robots have the potential to navigate in challenging terrain, and thus to exceed the mobility of wheeled vehicles. However, their control is more difficult as legged robots need to deal with foothold computation, leg trajectories and posture control in order to achieve successful navigation. In this paper, we present a new framework for the hydraulic quadruped robot HyQ, which performs goal-oriented navigation on unknown rough terrain using inertial measurement data and stereo-vision. This work uses our previously presented reactive controller framework with balancing control and extends it with visual feedback to enable closed-loop gait adjustment. On one hand, the camera images are used to keep the robot walking towards a visual target by correcting its heading angle if the robot deviates from it. On the other hand, the stereo camera is used to estimate the size of the obstacles on the ground plane and thus the terrain roughness. The locomotion controller then adjusts the step height and the velocity according to the size of the obstacles. This results in a robust and autonomous goal-oriented navigation over difficult terrain while subject to disturbances from the ground irregularities or external forces. Indoor and outdoor experiments with our quadruped robot show the effectiveness of this framework.