Robot Centered

Robot-centered research focuses on developing robotic systems and algorithms from the robot's perspective, optimizing performance and interaction based on the robot's sensory inputs and capabilities. Current research emphasizes improving robot perception through techniques like deep learning (e.g., convolutional neural networks and diffusion models) for tasks such as object detection, scene understanding, and egocentric gesture recognition, often incorporating novel metrics for safety and efficiency. This approach is crucial for advancing human-robot interaction, autonomous navigation, and collaborative tasks, leading to more robust and reliable robots in diverse real-world environments.