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Robust multi-sensor, day/night 6-DOF pose estimation for a dynamic legged vehicle in GPS-denied environments

Jeremy Ma, Sara Susca, Max Bajracharya, Larry Matthies, Matt Malchano, Dave Wooden

发表年份
2012
引用次数
57

摘要

We present a real-time system that enables a highly capable dynamic quadruped robot to maintain an accurate 6-DOF pose estimate (better than 0.5m over every 50m 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 units (IMU), and leg odometry with an Extended Kalman Filter (EKF) to ensure robust, low-latency performance. Extensive experimental results obtained from multiple field tests are presented to illustrate the performance and robustness of the system over hours of continuous runs over hundreds of meters of distance traveled in a wide variety of terrains and conditions.

关键词

Inertial measurement unitOdometryRobustness (evolution)Global Positioning SystemComputer scienceComputer visionKalman filterExtended Kalman filterArtificial intelligenceRobot

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