Vulcan Centaur: towards end-to-end real-time perception in lunar rovers
This work addresses the challenge of real-time perception for lunar rovers, specifically for the Iris Lunar Rover, representing an incremental step in robust autonomous navigation in extraterrestrial environments.
This paper introduces a real-time SLAM and VIO pipeline for planetary rovers, leveraging prior lander location information for object-level SLAM and employing image interpolation to enhance accuracy. The system is designed for the Iris Lunar Rover, set for lunar deployment in 2021.
We introduce a new real-time pipeline for Simultaneous Localization and Mapping (SLAM) and Visual Inertial Odometry (VIO) in the context of planetary rovers. We leverage prior information of the location of the lander to propose an object-level SLAM approach that optimizes pose and shape of the lander together with camera trajectories of the rover. As a further refinement step, we propose to use techniques of interpolation between adjacent temporal samples; videlicet synthesizing non-existing images to improve the overall accuracy of the system. The experiments are conducted in the context of the Iris Lunar Rover, a nano-rover that will be deployed in lunar terrain in 2021 as the flagship of Carnegie Mellon, being the first unmanned rover of America to be on the Moon.