Where to Map? Iterative Rover-Copter Path Planning for Mars Exploration
Not on the map. Why?
Abstract (arXiv)
In addition to conventional ground rovers, the Mars 2020 mission will send a helicopter to Mars. The copter's high-resolution data helps the rover to identify small hazards such as steps and pointy rocks, as well as providing rich textual information useful to predict perception performance. In this paper, we consider a three-agent system composed of a Mars rover, copter, and orbiter. The objective is to provide good localization to the rover by selecting an optimal path that minimizes the localization uncertainty accumulation during the rover's traverse. To achieve this goal, we quantify the localizability as a goodness measure associated with the map, and conduct a joint-space search over rover's path and copter's perceptual actions given prior information from the orbiter. We jointly address where to map by the copter and where to drive by the rover using the proposed iterative copter-rover path planner. We conducted numerical simulations using the map of Mars 2020 landing site to demonstrate the effectiveness of the proposed planner.
Key facts. Cited by 6 papers in the map (data through 13 Oct 2026). First posted on arXiv 17 Aug 2020.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 3; 2025: 0; 2026: 1.
6 papers.
- 2024RoboEXP: Action-Conditioned Scene Graph via Interactive Exploration for Robotic Manipulationcited by 48
- 2021NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challengecited by 32
- 2024General Place Recognition Survey: Towards Real-World Autonomycited by 23
- 2022General Place Recognition Survey: Towards the Real-world Autonomy Agecited by 11
- 2024When to Localize? A Risk-Constrained Reinforcement Learning Approachcited by 0
- 2026Rethinking Learned Occupancy in Autonomous Active Mapping with Observation-Gated Filteringcited by 0
- 2026Rethinking Learned Occupancy in Autonomous Active Mapping with Observation-Gated Filtering8 Sep 2026
- 2024When to Localize? A Risk-Constrained Reinforcement Learning Approach5 Nov 2024
- 2024General Place Recognition Survey: Towards Real-World Autonomy8 May 2024
- 2024RoboEXP: Action-Conditioned Scene Graph via Interactive Exploration for Robotic Manipulation23 Feb 2024
- 2022General Place Recognition Survey: Towards the Real-world Autonomy Age9 Sep 2022
- 2021NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challenge21 Mar 2021