ROAug 26, 2018

Sensor-based, time-critical mobility of autonomous robots in cluttered spaces: a harmonic potential approach

arXiv:1808.08582v14 citations
Originality Incremental advance
AI Analysis

This addresses the problem of efficient and safe navigation for autonomous robots in cluttered spaces, offering a practical solution for applications like search and rescue or logistics, though it appears incremental as it builds on harmonic potential field methods.

The paper tackles autonomous robot navigation in unknown cluttered environments by proposing an integrated system that enables time-critical mobility, allowing a robot to reach a target directly without prior mapping, using only local sensory data. The result is a well-behaved trajectory with minimal detours, validated through extensive experiments on the X80 robotic platform.

This paper suggests an integrated navigation system for an unmanned ground vehicle operating in an unknown cluttered environment. The navigator supports time-critical mobility making it possible for a mobile robot to reach a target from the first attempt without the need for a dedicated exploration and mapping stage. The robot only uses necessary and sufficient egocentric local sensory data collected on its way to the target. The construction of the navigation structure revolves around key properties of the harmonic potential field approach to motion planning. The robots trajectory is well-behaved and direct-to-the-goal. It contains only the minimum number of detours necessary to accommodate the sensory data and maintain the robot in a safe, goal-oriented state. The navigation structure is developed and its theoretical basis is explained. Extensive experimental validation of its properties and performance is carried-out using the X80 robotic platform

Foundations

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