Outputs (6)

Organisms as sensors in biohybrid entities as a novel tool for in-field aquatic monitoring (2023)
Journal Article
Rajewicz, W., Wu, C., Romano, D., Campo, A., Arvin, F., Casson, A. J., …Thenius, R. (2024). Organisms as sensors in biohybrid entities as a novel tool for in-field aquatic monitoring. Bioinspiration & Biomimetics, 19(1), Article 015001. https://doi.org/10.1088/1748-3190/ad0c5d

Rapidly intensifying global warming and water pollution calls for more efficient and continuous environmental monitoring methods. Biohybrid systems connect mechatronic components to living organisms and this approach can be used to extract data from... Read More about Organisms as sensors in biohybrid entities as a novel tool for in-field aquatic monitoring.

Distributed Bearing-Only Formation Control for Heterogeneous Nonlinear Multi-Robot Systems (2023)
Presentation / Conference Contribution
Wu, K., Hu, J., Ding, Z., & Arvin, F. (2023, July). Distributed Bearing-Only Formation Control for Heterogeneous Nonlinear Multi-Robot Systems

This paper addresses the bearing-only formation tracking problem for heterogeneous nonlinear multi-robot systems. In contrast to position and distance-based formation algorithms, the robots can only measure the bearing information from their neighbor... Read More about Distributed Bearing-Only Formation Control for Heterogeneous Nonlinear Multi-Robot Systems.

Unified Robust Path Planning and Optimal Trajectory Generation for Efficient 3D Area Coverage of Quadrotor UAVs (2023)
Journal Article
Rekabi-Bana, F., Hu, J., Krajník, T., & Arvin, F. (2024). Unified Robust Path Planning and Optimal Trajectory Generation for Efficient 3D Area Coverage of Quadrotor UAVs. IEEE Transactions on Intelligent Transportation Systems, 25(3), 2492-2507. https://doi.org/10.1109/tits.2023.3320049

Area coverage is an important problem in robotics applications, which has been widely used in search and rescue, offshore industrial inspection, and smart agriculture. This paper demonstrates a novel unified robust path planning, optimal trajectory g... Read More about Unified Robust Path Planning and Optimal Trajectory Generation for Efficient 3D Area Coverage of Quadrotor UAVs.

Reinforcement learning-based aggregation for robot swarms (2023)
Journal Article
Sadeghi Amjadi, A., Bilaloğlu, C., Turgut, A. E., Na, S., Şahin, E., Krajník, T., & Arvin, F. (2024). Reinforcement learning-based aggregation for robot swarms. Adaptive Behavior, 32(3), 265-281. https://doi.org/10.1177/10597123231202593

Aggregation, the gathering of individuals into a single group as observed in animals such as birds, bees, and amoeba, is known to provide protection against predators or resistance to adverse environmental conditions for the whole. Cue-based aggregat... Read More about Reinforcement learning-based aggregation for robot swarms.

Finite-Time Fault-Tolerant Formation Control for Distributed Multi-Vehicle Networks With Bearing Measurements (2023)
Journal Article
Wu, K., Hu, J., Ding, Z., & Arvin, F. (2024). Finite-Time Fault-Tolerant Formation Control for Distributed Multi-Vehicle Networks With Bearing Measurements. IEEE Transactions on Automation Science and Engineering, 21(2), 1346-1357. https://doi.org/10.1109/tase.2023.3239748

This paper addresses a bearing-only formation tracking problem in robotic networks by considering exogenous disturbances and actuator faults. In contrast to traditional position-based coordination strategies, the bearing-only coordinated movements of... Read More about Finite-Time Fault-Tolerant Formation Control for Distributed Multi-Vehicle Networks With Bearing Measurements.

Federated Reinforcement Learning for Collective Navigation of Robotic Swarms (2023)
Journal Article
Na, S., Roucek, T., Ulrich, J., Pikman, J., Krajnik, T., Lennox, B., & Arvin, F. (2023). Federated Reinforcement Learning for Collective Navigation of Robotic Swarms. IEEE Transactions on Cognitive and Developmental Systems, 15(4), 2122-2131. https://doi.org/10.1109/tcds.2023.3239815

The recent advancement of Deep Reinforcement Learning (DRL) contributed to robotics by allowing automatic controller design. The automatic controller design is a crucial approach for designing swarm robotic systems, which require more complex control... Read More about Federated Reinforcement Learning for Collective Navigation of Robotic Swarms.