Robot Performance

Robot performance research focuses on improving robots' capabilities across diverse tasks and environments, aiming to enhance efficiency, robustness, and reliability. Current efforts concentrate on developing advanced control algorithms (including reinforcement learning and multi-policy collaborations), optimizing hardware and software architectures (like FPGA integration and edge computing), and mitigating vulnerabilities (such as prompt injection attacks in LLM-integrated systems). These advancements are crucial for expanding the practical applications of robots in various sectors, from agriculture and manufacturing to healthcare and search and rescue, while also providing valuable insights into the fundamental challenges of autonomous systems.