Multi-robot cooperation for lunar In-Situ resource utilization.

This paper presents a cooperative, multi-robot solution for searching, excavating, and transporting mineral resources on the Moon. Our work was developed in the context of the Space Robotics Challenge Phase 2 (SRCP2), which was part of the NASA Centennial Challenges and was motivated by the current NASA Artemis program, a flagship initiative that intends to establish a long-term human presence on the Moon. In the SRCP2 a group of simulated mobile robots was tasked with reporting volatile locations within a realistic lunar simulation environment, and excavating and transporting these resources to target locations in such an environment. In this paper, we describe our solution to the SRCP2 competition that includes our strategies for rover mobility hazard estimation (e.g. slippage level, stuck status), immobility recovery, rover-to-rover, and rover-to-infrastructure docking, rover coordination and cooperation, and cooperative task planning and autonomy. Our solution was able to successfully complete all tasks required by the challenge, granting our team sixth place among all participants of the challenge. Our results demonstrate the potential of using autonomous robots for autonomous in-situ resource utilization (ISRU) on the Moon. Our results also highlight the effectiveness of realistic simulation environments for testing and validating robot autonomy and coordination algorithms. The successful completion of the SRCP2 challenge using our solution demonstrates the potential of cooperative, multi-robot systems for resource utilization on the Moon.

Slip-Based Autonomous ZUPT through Gaussian Process to Improve Planetary Rover Localization.

The zero-velocity update (ZUPT) algorithm provides valuable state information to maintain the inertial navigation system (INS) reliability when stationary conditions are satisfied. Employing ZUPT along with leveraging non-holonomic constraints can greatly benefit wheeled mobile robot dead-reckoning localization accuracy. However, determining how often they should be employed requires consideration to balance localization accuracy and traversal rate for planetary rovers. To address this, we investigate when to autonomously initiate stops to improve wheel-inertial odometry (WIO) localization performance with ZUPT. To do this, we propose a 3D dead-reckoning approach that predicts wheel slippage while the rover is in motion and forecasts the appropriate time to stop without changing any rover hardware or major rover operations. We validate with field tests that our approach is viable on different terrain types and achieves a 3D localization accuracy of ~97% over 650 m drives on rough terrain.