Research/ PLANETARY ROBOTICS
A GNC Architecture for Planetary Rovers with Autonomous Navigation Capabilities
Martin Azkarate, Levin Gerdes, Luc Joudrier, Carlos J. Pérez-del-Pulgar
Perception & State EstimationOpenAlex topic: Robotics and Sensor-Based Localization · Motion Planning & NavigationOpenAlex topic: Robotic Path Planning Algorithms · Surface Mobility & TerramechanicsOpenAlex keyword: terrain traversability
Perseverance (Mars 2020)named in abstract, keywords
arXivcs.ROOpenAlexRobotics and Sensor-Based Localization · Robotic Path Planning Algorithms · Reinforcement Learning in Robotics
This paper proposes a Guidance, Navigation, and Control (GNC) architecture for planetary rovers targeting the conditions of upcoming Mars exploration missions such as Mars 2020 and the Sample Fetching Rover (SFR). The navigation requirements of these missions demand a control architecture featuring autonomous capabilities to achieve a fast and long traverse. The proposed solution presents a two-level architecture where the efficient navigation (low) level is always active and the full navigation (upper) level is enabled according to the difficulty of the terrain. The first level is an efficient implementation of the basic functionalities for autonomous navigation based on hazard detection, local path replanning, and trajectory control with visual odometry. The second level implements an adaptive SLAM algorithm that improves the relative localization, evaluates the traversability of the terrain ahead for a more optimal path planning, and performs global (absolute) localization that corrects the pose drift during longer traverses. The architecture provides a solution for long range, low supervision and fast planetary exploration. Both navigation levels have been validated on planetary analogue field test campaigns.
Comments: Submission to RAL-ICRA2020. 6 pages + references
Journal ref: 2020 IEEE International Conference on Robotics and Automation (ICRA), 2020, pp. 3003-3009