Haptic Exploration

Haptic exploration focuses on using touch-based sensing to improve robots' understanding and manipulation of objects, particularly in situations where vision alone is insufficient. Current research emphasizes integrating haptic data with visual information, employing techniques like Bayesian optimization and Kalman filtering to efficiently guide exploration and improve object shape reconstruction using deep neural networks and implicit surface models. This work is significant for advancing robotic dexterity and robustness in tasks such as grasping and object recognition, particularly in unstructured or adversarial environments. Improved haptic exploration promises to enhance the capabilities of robots in various applications, from industrial automation to assistive technologies.