Bi Manual

Bimanual manipulation, the coordinated use of two robotic arms, aims to enable robots to perform complex tasks beyond the capabilities of single-arm systems. Current research focuses on improving the robustness and efficiency of bimanual control through techniques like multi-modal sensor fusion (e.g., combining RGB and depth data) and adaptive compliance methods, often implemented using reinforcement learning and neural networks such as LSTM and Actor-Critic architectures. These advancements are significant for expanding the capabilities of robots in manufacturing, space exploration, and other fields requiring dexterous manipulation, particularly in scenarios with perceptual challenges or the need for precise, adaptable control.