Decentralized Navigation

Decentralized navigation focuses on enabling multiple robots to navigate complex environments collaboratively without central coordination, aiming for efficient and collision-free movement. Current research emphasizes developing algorithms that leverage potential fields, reinforcement learning, and model predictive control, often incorporating learned barrier functions or medial axis representations to ensure safety and efficiency. These advancements improve task completion times and success rates in multi-robot systems, with applications ranging from warehouse automation to search and rescue operations.