Multi Robot
Multi-robot systems research focuses on coordinating multiple robots to achieve complex tasks more efficiently than single robots could. Current research emphasizes developing robust algorithms for tasks like collaborative mapping, target tracking, and exploration, often employing techniques like distributed optimization, reinforcement learning, and neural networks (including diffusion models and transformers) to handle challenges such as communication constraints, environmental uncertainties, and adversarial conditions. These advancements are significant for improving efficiency and reliability in various applications, including logistics, search and rescue, and environmental monitoring.
Papers
On Cyclic Solutions to the Min-Max Latency Multi-Robot Patrolling Problem
Peyman Afshani, Mark de Berg, Kevin Buchin, Jie Gao, Maarten Loffler, Amir Nayyeri, Benjamin Raichel, Rik Sarkar, Haotian Wang, Hao-Tsung Yang
Conservative Filtering for Heterogeneous Decentralized Data Fusion in Dynamic Robotic Systems
Ofer Dagan, Nisar R. Ahmed