As part of NASA's Mars 2020 rover Mission, an autonomous small-scale helicopter will be sent to Mars to conduct a series of demonstration flights, to validate the feasibility and utility of using helicopters for Mars exploration. In this paper, we present a high-level overview of the flight control system for the Mars Helicopter, including the Guidance, Navigation, and Control subsystems, and the implementation of these on the flight avionics hardware. We also discuss the concept of operations, and the testing, verification, and validation performed in a variety of test venues in preparation for Mars flight.
This paper presents a system for performing dense mapping of surface geometry and texture properties. Co-registered depth and grayscale images are incrementally fused into a global map in real-time as they are collected. The resulting dense map can be rendered into a virtual depth and grayscale image from any arbitrary pose. Comparison of the rendered and observed images provides a direct means of computing the sensor pose relative to the map allowing new data to be fused into the model. This frame-to-map tracking scheme, as opposed to frame-toframe tracking, improves system accuracy and robustness. Additionally, the use of both surface geometry and color texture better constrains the pose solution and reduces the risk of tracking failures. This paper describes an implementation of the proposed algorithm and provides experimental results.
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