This paper describes the stereo vision near-field terrain mapping system used by the Legged Squad Support System (LS3) quadruped vehicle to automatically adjust its gait in complex natural terrain. The mapping system achieves high robustness with a combination of stereo model-based outlier rejection and spatial and temporal filtering, enabled by a unique hybrid 2D/3D data structure. Classification of sparse structures allows the vehicle to traverse through vegetation. Inference of negative obstacles allows the vehicle to avoid steep drop-offs. A custom designed near-infrared illumination system enables operation at night. The mapping system has been tested extensively with controlled experiments and 72km of field testing in a wide variety of terrains and conditions.

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.

BigDog is a four legged robot with exceptional rough-terrain mobility. In this paper, we equip BigDog with a laser scanner, stereo vision system, and perception and navigation algorithms. Using these sensors and algorithms, BigDog performs autonomous navigation to goal positions in unstructured forest environments. The robot perceives obstacles, such as trees, boulders, and ground features, and steers to avoid them on its way to the goal. We describe the hardware and software implementation of the navigation system and summarize performance. During field tests in unstructured wooded terrain, BigDog reached its goal position 23 of 26 runs and traveled over 130 meters at a time without operator involvement.