On-line task allocation for the robotic interception of multiple targets in dynamic settings

Abstract

This paper presents a novel on-line optimal task-allocation methodology for the interception of a group of mobile targets by a team of robotic pursuers. The mobile targets are highly maneuverable. A rollinghorizon concept is used to increase the depth of the online search for the optimal solution. Guidance theory is utilized to navigate each pursuer independently toward its assigned target. Extensive simulations and experiments have confirmed the proposed generic

Autonomous Multi-Target Interception in Dynamic Settings – On-Line Pursuer Task Allocation

“…This module acts as a common point for data sharing across the system. In order to ensure that the most recent information is available, a Blackboard Approach is used to store, update, and publish new target/pursuer state information [3]. Four specific data structures are updated onto and read from the Blackboard, as shown in Table 1.…”

“…Teams of autonomous agents are used in applications where the task at hand may be too complex for one agent to achieve efficiently, including multi-target search and rescue, surveillance and tracking, and target interception (e.g., [1][2][3]). The agents (which we define here as pursuers) operate in dynamic environments, where they localize or intercept moving targets of interest.…”

“…In this paper, we present a generic task-allocation methodology that allows a team of autonomous robotic pursuers to optimally intercept multiple mobile targets in a time efficient manner within dynamic environments, first addressed by us in [3]. Furthermore, the proposed methodology re-pairs pursuers and targets as needed in an on-line manner.…”

Tracking and intercepting pedestrians: a robotic approach to surveillance of critical infrastructures

“…The interception of a group of mobile targets by a team of robotic pursuers has been also studied, one work integrates genetic algorithms and fuzzy logic controllers to solve it [101]. Another uses centralized optimization techniques for pursuertarget assignments, and time-optimal guidance for interception [102]. However, the methods based on fuzzy control require a high number of rules that are obtained after trial and error experiments, and they will not adapt easily to significant changes in the settings of the scenario or the experiment.…”