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Mixed Controller Design for Multi-Vehicle Formation Based on Edge and Bearing Measurements (2022)
Conference Proceeding
Wu, K., Hu, J., Lennox, B., & Arvin, F. (2022). Mixed Controller Design for Multi-Vehicle Formation Based on Edge and Bearing Measurements. In 2022 European Control Conference (ECC). https://doi.org/10.23919/ecc55457.2022.9838436

Inspired by natural swarm collective behaviors such as colonies of bees and schools of fish, coordination strategies in swarm robotics have received significant attention in recent years. In this paper, a mixed formation control design based on edge... Read More about Mixed Controller Design for Multi-Vehicle Formation Based on Edge and Bearing Measurements.

Distributed Motion Planning for Safe Autonomous Vehicle Overtaking via Artificial Potential Field (2022)
Journal Article
Xie, S., Hu, J., Bhowmick, P., Ding, Z., & Arvin, F. (2022). Distributed Motion Planning for Safe Autonomous Vehicle Overtaking via Artificial Potential Field. IEEE Transactions on Intelligent Transportation Systems, 23(11), 21531- 21547. https://doi.org/10.1109/tits.2022.3189741

Autonomous driving of multi-lane vehicle platoons have attracted significant attention in recent years due to their potential to enhance the traffic-carrying capacity of the roads and produce better safety for drivers and passengers. This paper propo... Read More about Distributed Motion Planning for Safe Autonomous Vehicle Overtaking via Artificial Potential Field.

A Minimally Invasive Approach Towards “Ecosystem Hacking” With Honeybees (2022)
Journal Article
Stefanec, M., Hofstadler, D. N., Krajník, T., Turgut, A. E., Alemdar, H., Lennox, B., …Schmickl, T. (2022). A Minimally Invasive Approach Towards “Ecosystem Hacking” With Honeybees. Frontiers in Robotics and AI, 9, Article 791921. https://doi.org/10.3389/frobt.2022.791921

Honey bees live in colonies of thousands of individuals, that not only need to collaborate with each other but also to interact intensively with their ecosystem. A small group of robots operating in a honey bee colony and interacting with the queen b... Read More about A Minimally Invasive Approach Towards “Ecosystem Hacking” With Honeybees.

Fault-tolerant cooperative navigation of networked UAV swarms for forest fire monitoring (2022)
Journal Article
Hu, J., Niu, H., Carrasco, J., Lennox, B., & Arvin, F. (2022). Fault-tolerant cooperative navigation of networked UAV swarms for forest fire monitoring. Aerospace Science and Technology, 123, Article 107494. https://doi.org/10.1016/j.ast.2022.107494

Coordination of unmanned aerial vehicle (UAV) swarms has received significant attention due to its wide practical applications including search and rescue, cooperative exploration and target surveillance. Motivated by the flexibility of the UAVs and... Read More about Fault-tolerant cooperative navigation of networked UAV swarms for forest fire monitoring.

Robust formation control for networked robotic systems using Negative Imaginary dynamics (2022)
Journal Article
Hu, J., Lennox, B., & Arvin, F. (2022). Robust formation control for networked robotic systems using Negative Imaginary dynamics. Automatica, 140, Article 110235. https://doi.org/10.1016/j.automatica.2022.110235

This paper proposes a consensus-based formation tracking scheme for multi-robot systems utilizing the Negative Imaginary (NI) theory. The proposed scheme applies to a class of networked robotic systems that can be modelled as a group of single integr... Read More about Robust formation control for networked robotic systems using Negative Imaginary dynamics.

Bio-Inspired Collision Avoidance in Swarm Systems via Deep Reinforcement Learning (2022)
Journal Article
Na, S., Niu, H., Lennox, B., & Arvin, F. (2022). Bio-Inspired Collision Avoidance in Swarm Systems via Deep Reinforcement Learning. IEEE Transactions on Vehicular Technology, 71(3), 2511-2526. https://doi.org/10.1109/tvt.2022.3145346

Autonomous vehicles have been highlighted as a major growth area for future transportation systems and the deployment of large numbers of these vehicles is expected when safety and legal challenges are overcome. To meet the necessary safety standards... Read More about Bio-Inspired Collision Avoidance in Swarm Systems via Deep Reinforcement Learning.