Robot Centric

Robot-centric approaches in robotics focus on building representations of the environment from the robot's perspective, enabling robust navigation and mapping in dynamic and complex settings. Current research emphasizes real-time perception using techniques like structure flow and implicit neural representations, often integrated with reinforcement learning for improved navigation in challenging terrains. These advancements are crucial for improving autonomous robot capabilities in applications such as autonomous driving, mobile manipulation, and swarm robotics, leading to more efficient and reliable systems. The development of lightweight, robust, and scalable methods remains a key focus.