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About

Michael Jokesch is a robotics researcher whose work centers on advancing autonomous assembly, sensor integration, and tactile perception for industrial robots. His most significant contribution is a generic algorithm for peg-in-hole assembly tasks with impedance controlled robots, a foundational paper that has garnered 24 citations and addresses a classic challenge in precision manufacturing. Jokesch further enhanced assembly reliability by combining particle filters with haptic rendering models derived solely from CAD data, enabling error-tolerant manipulation without physical trials. In the domain of tactile sensing, he developed an optical tactile sensor capable of measuring both force values and directions for soft and rigid contacts—a critical innovation for handling fragile objects, earning 11 citations. His work also integrates vision and force control to transport objects of varying shapes and colors from moving circular conveyors, demonstrating practical industrial automation. Through these contributions, Jokesch has established himself as a researcher focused on bridging simulation, sensing, and real-world robotic dexterity, with a clear impact on improving the adaptability and robustness of robotic systems in complex assembly and handling tasks.