Motivation Dynamics for Autonomous Composition of Navigation tasks

Paul B. Reverdy, Vasileios Vasilopoulos, Daniel E. Koditschek

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

In this article, we physically demonstrate a reactive sensorimotor architecture for mobile robots whose behaviors are generated by motivation dynamics. Motivation dynamics uses a continuous dynamical system to reactively compose low-level control vector fields using valuation functions that capture the potentially competing influences of external stimuli relative to the system's own internal state. We show that motivation dynamics naturally accommodates external stimuli through standard signal processing tools, and can effectively encode a repetitive higher level task by composing several low-level controllers to achieve a limit cycle in which the robot repeatedly navigates toward two alternatively valuable goal locations in a commensurately alternating order. We show that these behaviors are robust to perturbations, including imperfect models of robot kinematics, sensor noise, and disturbances, resulting from the need to traverse difficult terrain. We argue that motivation dynamics can provide a useful alternative to controllers based on hybrid automata in situations where the control operates at a low level close to the physical hardware.

Original languageEnglish (US)
Article number9380469
Pages (from-to)1239-1251
Number of pages13
JournalIEEE Transactions on Robotics
Volume37
Issue number4
DOIs
StatePublished - Aug 2021

Keywords

  • Autonomous systems
  • nonlinear control systems
  • nonlinear dynamical systems
  • path planning

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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