This paper revises and evaluates an orbital emulator (OE) for space situational awareness (SSA). The OE can produce 3D satellite movements using capabilities generated from omni-wheeled robot and robotic arm motions. The 3D motion of satellite is partitioned into the movements in the equatorial plane and the up-down motions in the vertical plane. The 3D actions are emulated by omni-wheeled robot models while the up-down motions are performed by a stepped-motorcontrolled- ball along a rod (robotic arm), which is attached to the robot. Lidar only measurements are used to estimate the pose information of the multiple robots. SLAM (simultaneous localization and mapping) is running on one robot to generate the map and compute the pose for the robot. Based on the SLAM map maintained by the robot, the other robots run the adaptive Monte Carlo localization (AMCL) method to estimate their poses. The controller is designed to guide the robot to follow a given orbit. The controllability is analyzed by using a feedback linearization method. Experiments are conducted to show the convergence of AMCL and the orbit tracking performance.
Dan Shen, Xingyu Xiang, Bin Jia, Zhonghai Wang, Genshe Chen, Erik Blasch, and Khanh Pham, "A robotic orbital emulator with lidar-based SLAM and AMCL for multiple entity pose estimation," Proc. SPIE 10641, Sensors and Systems for Space Applications XI, 106410E (Presented at SPIE Defense + Security: April 16, 2018; Published: 10 May 2018); https://doi.org/10.1117/12.2304878.
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