Abstract-Autonomous rendezvous and docking is necessary for planned space programs such as DARPA ASTRO, NASA MSR, ISS assembly and servicing, and other rendezvous and proximity operations. Estimation of the relative pose between the host platform and a resident space object is a critical ability. We present a model-based pose refinement algorithm, part of a suite of algorithms for vision-based relative pose estimation and tracking. Algorithms were tested in highfidelity simulation and stereo-vision hardware testbed environments. Testing indicated that in most cases, the modelbased pose refinement algorithm can handle initial attitude errors up to about 20 degrees, range errors exceeding 10% of range, and transverse errors up to about 2% of range. Preliminary point tests with real camera sequences of a 1/24 scale Magellan satellite model using a simple fixed-gain tracking filter showed potential tracking performance with mean errors of < 3 degrees and < 2% of range.

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This paper presents experimental results for the simultaneous intercept of preassigned targets by a team of mobile robots. The robots are programmed to mimic the dynamic behavior of unmanned air vehicles in constant-altitude flight. In proceeding to their targets, robots must avoid both known static threats and pop-up threats. An overview of the cooperative control strategy followed is given, as well as a description of the robot hardware and software used. Experimental results demonstrating simultaneous intercept of targets by the robot team are presented.

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