Adaptive Headway Motion Control and Motion Prediction for Safe Unicycle Motion Design

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Abstract

Differential drive robots that can be modeled as a kinematic unicycle are a standard mobile base platform for many service and logistics applications. Safe and smooth autonomous motion around obstacles is a crucial skill for unicycle robots to perform diverse tasks in complex environments. A classical control approach for unicycle control is feedback linearization using a headway point at a fixed headway distance in front of the unicycle. The unicycle headway control brings the headway point to a desired goal location by embedding a linear headway reference dynamics, which often results in an undesired offset for the actual unicycle position. In this paper, we introduce a new unicycle headway control approach with an adaptive headway distance that overcomes this limitation, i.e., when the headway point reaches the goal the unicycle position is also at the goal. By systematically analyzing the closed-loop unicycle motion under the adaptive headway controller, we design analytical feedback motion prediction methods that bound the closed-loop unicycle position trajectory and so can be effectively used for safety assessment and safe unicycle motion design around obstacles. We present an application of adaptive headway motion control and motion prediction for safe unicycle path following around obstacles in numerical simulations.

Original languageEnglish
Title of host publication2023 62nd IEEE Conference on Decision and Control, CDC 2023
PublisherInstitute of Electrical and Electronics Engineers
Pages6942-6949
Number of pages8
ISBN (Electronic)979-8-3503-0124-3
DOIs
Publication statusPublished - 19 Jan 2024
Event62nd IEEE Conference on Decision and Control, CDC 2023 - Singapore, Singapore
Duration: 13 Dec 202315 Dec 2023
Conference number: 62

Conference

Conference62nd IEEE Conference on Decision and Control, CDC 2023
Abbreviated titleCDC 2023
Country/TerritorySingapore
CitySingapore
Period13/12/2315/12/23

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