Grants and Contributions:

Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023)

The main objective of the proposed research is to develop novel real-time computational-intelligence tactile feedback-based control algorithms for a human-like multi-finger robot hand able to dexterously explore, grasp, and in-hand manipulate 3D objects.
Dexterous object exploration, grasping and manipulation is a complex area of robotics in which multiple fingers cooperate to carry out the task. Controlling a dexterous robotic hand poses major design challenges for the tactile sensors that are the first line of contact, for processing the sensor data, detecting object geometry, slippage and contact pressure, and then for the tactile and kinaesthetic feedback-based coordinated control of all finger movements and applied forces.
The short-term objectives are (1) development of new algorithms for the fusion of tactile- and kinaesthetic-sensor data to provide a coherent multisensory feedback for the real-time control of the dexterous robot hand, (2) development of new neuro-fuzzy reactive-behavior control algorithms for concurrent position & force control of hand fingers during object exploration, and (3) development of task-driven intelligent control algorithms for dexterous object grasping and in-hand manipulation
The new intelligent tactile-based hand control techniques to be studied will have a significant impact on an emerging range of robotics applications requiring advanced dexterous object exploration, grasping, and manipulation capabilities such as: (i) autonomous or remotely controlled robotic handling of materials in hazardous environments, high risk war-zone and security operations, or difficult to reach undersea and outer space environments, (ii) tele-surgery and tele-medical diagnostic, (iii) a new generation of humanoid robots for eldercare assistance and social robotics.