SMUG Planner: A Safe Multi-Goal Planner for Mobile Robots in Challenging Environments


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Date

2023-11

Publication Type

Journal Article

ETH Bibliography

yes

Citations

Altmetric

Data

Abstract

Robotic exploration or monitoring missions require mobile robots to autonomously and safely navigate between multiple target locations in potentially challenging environments. Currently, this type of multi-goal mission often relies on humans designing a set of actions for the robot to follow in the form of a path or waypoints. In this letter, we consider the multi-goal problem of visiting a set of pre-defined targets, each of which could be visited from multiple potential locations. To increase autonomy in these missions, we propose a safe multi-goal (SMUG) planner that generates an optimal motion path to visit those targets. To increase safety and efficiency, we propose a hierarchical state validity checking scheme, which leverages robot-specific traversability learned in simulation. We use LazyPRM* with an informed sampler to accelerate collision-free path generation. Our iterative dynamic programming algorithm enables the planner to generate a path visiting more than ten targets within seconds. Moreover, the proposed hierarchical state validity checking scheme reduces the planning time by 30% compared to pure volumetric collision checking and increases safety by avoiding high-risk regions. We deploy the SMUG planner on the quadruped robot ANYmal and show its capability to guide the robot in multi-goal missions fully autonomously on rough terrain.

Publication status

published

Editor

Book title

Volume

8 (11)

Pages / Article No.

7170 - 7177

Publisher

IEEE

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Constrained motion planning; Motion and path planning

Organisational unit

09570 - Hutter, Marco / Hutter, Marco check_circle

Notes

Funding

101016970 - Natural Intelligence for Robotic Monitoring of Habitats (EC)

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