Tactile Sensing and Contact Modeling
Tactile perception and contact modeling are crucial for successful manipulation tasks, as they enable robots to understand and interact with their environment through touch. By sensing tactile information, robots can perceive object properties, detect contacts, and adjust their grasp and movement accordingly. This integration of tactile sensing and visual observation enhances robot dexterity, stability, and overall performance in contact-rich manipulation scenarios.
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Soft Material Modeling and Manipulation
Learning control strategies to manipulate soft materials (e.g., cables, papers) is challenging and the behaviors of soft materials under contact are difficult to model. Collaborating with MIT-IBM Watson AI Lab, we presented a fully differentiable simulation platform for thin-shell object manipulation tasks (e.g., papers) and a differentiable simulation environment for vision-based tactile sensors (e.g., GelSight) for learning robotic skills efficiently in simulation.
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