Robot Behaviour Model

Robot behavior modeling aims to create autonomous robots capable of executing complex tasks and interacting naturally with humans, often based on natural language instructions or multimodal sensory input. Current research heavily utilizes deep generative models, including GANs, diffusion models, and energy-based models, to learn complex behaviors from large datasets of demonstrations, often incorporating techniques like reinforcement learning and motion primitives for improved control and explainability. This field is crucial for advancing robotics in various sectors, from industrial automation to assistive technologies, particularly in applications like robot-assisted therapy where personalized behavior models are increasingly important.