Distributed Parameterized Predictive Control for Multi-robot Curve Tracking

Author(s)

Pacheco, Gabriel, V ; Pimenta, Luciano C. A. ; Raffo, Guilherme, V

• Document type: Journal article
• Source: IFAC PAPERSONLINE; v. 53, n. 2, p. 6-pg., 2020-01-01.

Abstract

This work proposes a guidance strategy of multiple robots to converge and circulate a curve while avoiding collisions by using a distributed model predictive control. To build the model predictive control framework, systems guided by control laws with parameters are considered, which laws are embedded in the optimization problem. After that, the same problem is distributed using the Alternating Direction Method of Multipliers and nonlinear optimization. To solve the task of convergence and circulation of a closed path, a vector field based control law is embedded in the predictive control scheme. The control law results from the sum of two components, a convergence term and a circulation term, whereas each term has one proportional parameter associated. Numerical results present an application example, and the strategy effectiveness is discussed. Copyright (C) 2020 The Authors. (AU)

• FAPESP's process: 14/50851-0 - INCT 2014: National Institute of Science and Technology for Cooperative Autonomous Systems Applied in Security and Environment
• Grantee: Marco Henrique Terra
• Support Opportunities: Research Projects - Thematic Grants