Collaborator: A Nonholonomic Multiagent Team for Tasks in a Dynamic Environment

In our previous work, we proposed a potential field-based hybrid path planning scheme for robot navigation that achieves complete coverage in various tasks. Thispaper is an extension of this work producing a multiagent framework, Collaborator, that integrates a high-level negotiation-based task allocation protocol with alow-level path planning method taking into consideration several real-world robotlimitations such as nonholonomic constraints. Specifically, the proposed frameworkfocuses on a class of complex motion planning problems in which robots need tocover the whole workspace, coordinate the accomplishment of a task, and dynamically change their roles to best fit the task. Applications in this class of problemsinclude bomb detection and removal as well as rescuing of survivors from accidentsor disasters. We have tested the framework in simulations of several tasks and haveshown that Collaborator can satisfy nonholonomic constraints, cooperatively accomplish given tasks in an initially unknown dynamic environment while avoidingcollision with other team members. Finally we prove that the proposed control lawsare stable using the Lyapunov stability theory.