Page 4: Research news on Embodied robotic manipulation

Embodied robotic manipulation investigates robotic and prosthetic limbs that physically interact with the environment using human-like, adaptive control. Work in this area integrates soft robotic structures, tendon-driven and biohybrid actuators, and exoskeletons with rich multimodal sensing, including vision, tactile, and proprioceptive feedback. Machine learning methods such as imitation learning, reinforcement learning, and meta-learning are used to acquire dexterous skills, enable shared and autonomous control, and support intuitive human–robot interaction through haptic interfaces, brain–computer interfaces, and teleoperation systems.

Robotics

Closing the gap between animal movement and robotic control

Animals move with a level of precision and adaptability that robots struggle to match. In Carnegie Mellon University's Department of Mechanical Engineering, researchers are developing a new AI-driven approach to uncover how ...

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