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Multi-Objective Global Path Planning for Lunar Exploration With a Quadruped Robot

Julia Richter, Hendrik Kolvenbach, Giorgio Valsecchi, Marco Hutter

Abstract

In unstructured environments the best path is not always the shortest, but needs to consider various objectives like energy efficiency, risk of failure or scientific outcome. This paper proposes a global planner, based on the A* algorithm, capable of individually considering multiple layers of map data for different cost objectives. We introduce weights between the objectives, which can be adapted to achieve a variety of optimal paths. In order to find the best of these paths, a tool for statistical path analysis is presented. Our planner was tested on exemplary lunar topographies to propose two trajectories for exploring the Aristarchus Plateau. The optimized paths significantly reduce the risk of failure while yielding more scientific value compared to a manually planned paths in the same area. The planner and analysis tool are made open-source in order to simplify mission planning for planetary scientists.

Multi-Objective Global Path Planning for Lunar Exploration With a Quadruped Robot

Abstract

In unstructured environments the best path is not always the shortest, but needs to consider various objectives like energy efficiency, risk of failure or scientific outcome. This paper proposes a global planner, based on the A* algorithm, capable of individually considering multiple layers of map data for different cost objectives. We introduce weights between the objectives, which can be adapted to achieve a variety of optimal paths. In order to find the best of these paths, a tool for statistical path analysis is presented. Our planner was tested on exemplary lunar topographies to propose two trajectories for exploring the Aristarchus Plateau. The optimized paths significantly reduce the risk of failure while yielding more scientific value compared to a manually planned paths in the same area. The planner and analysis tool are made open-source in order to simplify mission planning for planetary scientists.
Paper Structure (19 sections, 17 equations, 7 figures, 4 tables)

This paper contains 19 sections, 17 equations, 7 figures, 4 tables.

Table of Contents

  1. INTRODUCTION
  2. RELATED WORK
  3. METHODS
  4. Customized Cost Function
  5. Specific Cost Components
  6. Heuristic Function
  7. Path Evaluation
  8. Statistical Analysis
  9. RESULTS
  10. Map Data
  11. Run Time Analysis
  12. General Performance Analysis
  13. Statistical Path Analysis
  14. Proposed Exploration Missions
  15. DISCUSSION
  16. ...and 4 more sections

Figures (7)

  • Figure 1: Satellite images of scientifically interesting regions around the Aristarchus crater, featuring Aristarchus IMP (IMP) and Herodotus Mons (HM). Figures b and d show paths created by a lunar geology expert, while the paths in Figures c and e were generated using our proposed path planning tool.
  • Figure 2: Global path calculation pipeline with multi-objective cost
  • Figure 3: Plotted distribution of weights $\alpha_m$ with $0\leq \alpha_m \leq 1$, $\sum\alpha_m = 1$ and $m=1,2,3$
  • Figure 4: Map layers for two mission scenarios
  • Figure 5: Results of path planning for selected weights on Aristarchus IMP
  • ...and 2 more figures