Multi-Robot Multi-Goal Mission Planning in Terrains of Varying Energy Consumption

This paper considers planning missions for a fleet of robots with limited energy. Each robot has size, heading, and velocity and its motion is described by non-linear differential equations. The dynamics of movements, existing obstacles, multiple robots, and waypoints are additional challenges, as the combined task and motion planning procedure prevents collisions. On their long-term missions, robots have to visit several waypoints in a cost-minimizing manner to satisfy the overall mission task. The robots consume energy and have to be recharged. The framework guides expanding a motion tree via a state projection to a discrete problem, whose solutions serve as search heuristics. Our experiments highlight that despite all these challenges, even sizable problem tasks can be solved even for complex environments.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10802578
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
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article

Multi-Robot Multi-Goal Mission Planning in Terrains of Varying Energy Consumption

Jáchym Herynek, Stefan Edelkamp
Robotic Path Planning Algorithms
article

Multi-Robot Multi-Goal Mission Planning in Terrains of Varying Energy Consumption

Jáchym Herynek, Stefan Edelkamp
article en

Abstract

This paper considers planning missions for a fleet of robots with limited energy. Each robot has size, heading, and velocity and its motion is described by non-linear differential equations. The dynamics of movements, existing obstacles, multiple robots, and waypoints are additional challenges, as the combined task and motion planning procedure prevents collisions. On their long-term missions, robots have to visit several waypoints in a cost-minimizing manner to satisfy the overall mission task. The robots consume energy and have to be recharged. The framework guides expanding a motion tree via a state projection to a discrete problem, whose solutions serve as search heuristics. Our experiments highlight that despite all these challenges, even sizable problem tasks can be solved even for complex environments.

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Robotic Path Planning Algorithms
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