Next Article in Journal
MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory
Previous Article in Journal
Tutorial Review on Space Manipulators for Space Debris Mitigation
Open AccessFeature PaperArticle

A Time-Efficient Co-Operative Path Planning Model Combined with Task Assignment for Multi-Agent Systems

Defence Force Academy, University of New South Wales, 2052 Canberra, Australia
*
Author to whom correspondence should be addressed.
Robotics 2019, 8(2), 35; https://doi.org/10.3390/robotics8020035
Received: 15 March 2019 / Revised: 19 April 2019 / Accepted: 23 April 2019 / Published: 26 April 2019
Dealing with uncertainties along with high-efficiency planning for task assignment problem is still challenging, especially for multi-agent systems. In this paper, two frameworks—Compromise View model and the Nearest-Neighbour Search model—are analyzed and compared for co-operative path planning combined with task assignment of a multi-agent system in dynamic environments. Both frameworks are capable of dynamically controlling a number of autonomous agents to accomplish multiple tasks at different locations. Furthermore, these two models are capable of dealing with dynamically changing environments. In both approaches, the Particle Swarm Optimization-based method is applied for path planning. The path planning approach combined with the obstacle avoidance strategy is integrated with the task assignment problem. In one framework, the Compromise View model is used for completing the tasks and a combination of clustering method with the Nearest-Neighbour Search model is used to assign tasks to the other framework. The frameworks are compared in terms of computational time and the resulting path length. Results indicate that the Nearest-Neighbour Search model is much faster than the Compromise View model. However, the Nearest-Neighbour Search model generates longer paths to accomplish the mission. By following the Nearest-Neighbour Search approach, agents can successfully accomplish their mission, even under uncertainties such as malfunction of individual agents. The Nearest-Neighbour Search framework is highly effective due to its reactive structure. As per requirements, to save time, after completing its own tasks, one agent can complete the remaining tasks of other agents. The simulation results show that the Nearest-Neighbour Search model is an effective and robust way of solving co-operative path planning combined with task assignment problems. View Full-Text
Keywords: multi-agent system; task assignment; path planning; dynamically changing environments multi-agent system; task assignment; path planning; dynamically changing environments
Show Figures

Figure 1

MDPI and ACS Style

Biswas, S.; Anavatti, S.G.; Garratt, M.A. A Time-Efficient Co-Operative Path Planning Model Combined with Task Assignment for Multi-Agent Systems. Robotics 2019, 8, 35.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop