Navigation Behavior

Robot navigation research focuses on enabling autonomous robots to move safely and efficiently in diverse environments, often prioritizing alignment with human intentions and social norms. Current efforts leverage machine learning, particularly deep reinforcement learning and model predictive control, often incorporating multimodal perception (e.g., vision and LiDAR) and novel architectures like transformers and graph neural networks to achieve robust and socially compliant navigation. This field is crucial for advancing robotics in various sectors, including healthcare, logistics, and assistive technologies, by creating robots that can seamlessly interact with and navigate complex human-centered spaces.