Real-time pose estimation of a dynamic quadruped in GPS-denied environments for 24-hour operation

作者：Jeremy Ma, Max Bajracharya, Sara Susca, Larry Matthies, Matt Malchano · 发表于：The International Journal of Robotics Research · 年份：2015 · DOI：10.1177/0278364915587333 · 被引用次数：46 · 研究领域：Robotics and Sensor-Based Localization、Robotic Locomotion and Control、Indoor and Outdoor Localization Technologies

We present a real-time system that enables a highly capable dynamic quadruped robot to maintain an accurate six-degree-of-freedom pose estimate (within a 1.0% error of distance traveled) over long distances traversed through complex, dynamic outdoor terrain, during day and night, in the presence of camera occlusion and saturation, and occasional large external disturbances, such as slips or falls. The system fuses a stereo-camera sensor, inertial measurement unit, leg odometry, and optional intermittent GPS position updates with an extended Kalman filter to ensure robust, low-latency performance. To maintain a six-degree-of-freedom local positioning accuracy alongside the global positioning knowledge, two reference frames are used; a local reference frame and a global reference frame, with the former benefiting obstacle detection and mapping and the latter for operator-specified and autonomous way-point following. Extensive experimental results obtained from multiple field tests are presented to illustrate the performance and robustness of the system over hours of continuous runs and hundreds of kilometers of distance traveled in a wide variety of terrains and conditions.