Robot Formation

Robot formation research focuses on coordinating multiple robots to achieve a desired spatial arrangement, enabling collaborative tasks and enhanced capabilities beyond individual robots. Current research emphasizes developing algorithms for automated formation creation from natural language instructions or optimized cost functions balancing task requirements and sensing accuracy, often employing techniques like reinforcement learning, model predictive control, and vision-language models. These advancements are significant for applications ranging from infrastructure inspection and micro-assembly to swarm robotics and cooperative object manipulation, improving efficiency and robustness in complex environments.