Where to Map? Iterative Rover-Copter Path Planning for Mars Exploration

Abstract

In addition to conventional ground rovers, the Mars 2020 mission will send a helicopter to Mars. The copter's highresolution 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.

Collaborative Rover-copter Path Planning and Exploration with Temporal Logic Specifications Based on Bayesian Update Under Uncertain Environments

“…Several motion planning/exploration techniques employing the rover-copter collaboration have been provided, see, e.g., [4][5][6]. In particular, our approach is closely related to [4], in the sense that the overall synthesis problem is decomposed into two sub-problems, i.e., the problem of synthesizing a copter's exploration policy in the uncertain environment, and the problem of synthesizing the optimal policy for the rover so as to satisfy the scLTL formula.…”

“…In particular, to investigate Martian geology and habitability, NASA has decided to send copters to Mars in order to help the rover discover target samples in an efficient way [3]. Motivated by this fact, several motion planning techniques employing the rover-copter collaboration for the Mars exploration have been investigated in recent years, see, e.g., [4][5][6].…”

Exploração autônoma de ambientes planares utilizando um dispositivo robótico móvel

“…A exploração pode ser definida como a tarefa de navegar em um ambiente desconhecido, construindo um mapa de maneira iterativa, que é utilizado para a navegação subsequente. Mais recentemente, os avanços na exploração envolvem métodos melhorados de planejamento de caminhos (Reinhart et al, 2020) e cooperação entre robôs heterogêneos, como um helicóptero e um rover para exploração planetária (Sasaki et al, 2020) e subterrânea (Rouček et al, 2019;Ebadi et al, 2020). A exploração está diretamente ligada ao problema de localização e mapeamento simultâneos (em inglês Simultaenous Localization and Mapping, ou SLAM), que consiste em construir um mapa de um ambiente desconhecido e ao mesmo tempo estimar a localização do agente dentro desse mapa.…”

Autonomous Spot: Long-Range Autonomous Exploration of Extreme Environments with Legged Locomotion

“…Autonomous robot mapping and traversal of extreme environments under time constraints has a wide variety of real-world applications, including search and rescue after natural disasters [1], exploration of extreme planetary terrains [2], [3], [4], and inspection of urban underground environments [5]. As a concrete mission, we focus on the DARPA Subterranean (SubT) Challenge [6]: a robotic competition that targets missions to explore, map, and search extreme underground environments.…”