Active camera stabilization to enhance the vision of agile legged robots. Issue 4 (17th November 2015)

• Record Type: Journal Article
• Authors: Bazeille, Stéphane; Ortiz, Jesus; Rovida, Francesco; Camurri, Marco; Meguenani, Anis; Caldwell, Darwin G.; Semini, Claudio
• Is Part Of: Robotica. Volume 35:Issue 4(2017)
• Page Start: 942
• Page End: 960
• Publication Date: 2015-11-17
• Subjects: Stereo vision, -- Camera stabilization, -- Active head, -- Simultaneous localization and mapping (SLAM), -- Color tracking, -- Quadruped robot; Robots -- Periodicals; 629.89205
• DOI: 10.1017/S0263574715000909
• Languages: English
• ISSNs: 0263-5747

Abstract

SUMMARY: Legged robots have the potential to navigate in more challenging terrains than wheeled robots. Unfortunately, their control is more demanding, because they have to deal with the common tasks of mapping and path planning as well as more specific issues of legged locomotion, like balancing and foothold planning. In this paper, we present the integration and the development of a stabilized vision system on the fully torque-controlled hydraulically actuated quadruped robot (HyQ). The active head added onto the robot is composed of a fast pan and tilt unit (PTU) and a high-resolution wide angle stereo camera. The PTU enables camera gaze shifting to a specific area in the environment (both to extend and refine the map) or to track an object while navigating. Moreover, as the quadruped locomotion induces strong regular vibrations, impacts or slippages on rough terrain, we took advantage of the PTU to mechanically compensate for the robot's motions. In this paper, we demonstrate the influence of legged locomotion on the quality of the visual data stream by providing a detailed study of HyQ's motions, which are compared against a rough terrain wheeled robot of the same size. Our proposed Inertial Measurement Unit (IMU)-based controller allows us to decouple the camera from the robot motions. We show through experiments that, by stabilizing the image feedback, we can improve the onboard vision-based processes of tracking and mapping. In particular, during the outdoor tests on the quadruped robot, the use of our camera stabilization system improved the accuracy on the 3D maps by 25%, with a decrease of 50% of mapping failures.