Prof. Marko Popovic Profile

Prof. Marko Popovic

at Worcester Polytechnic Institute

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Publications (2)

Proceedings Article | 28 April 2023 Presentation + Paper

Sensitive robust tactile fingertips and shape-morphing actuation for robotic grippers

Calum Briggs, Yanni Sporidis, Peter Vicars, Lenore Rasmussen, Marko Popovic, Matthew Bowers

Proceedings Volume 12482, 1248209 (2023) https://doi.org/10.1117/12.2658596

KEYWORDS: Robotics, Electroactive polymers, Sensors, Robots, Polymers, Muscles, Actuators, Electrodes, Design and modelling

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Proceedings Article | 20 April 2022 Presentation + Paper

Sensitive and robust electroactive polymer tactile pressure sensors and shape-morphing actuation for robotic grippers

Calum Briggs, Greg Kaiser, Yanni Sporidis, Peter Vicars, Lenore Rasmussen, Matthew Bowers, Ada Dogrucu, Marko Popovic, Alexander Zhong

Proceedings Volume 12042, 120420I (2022) https://doi.org/10.1117/12.2607779

KEYWORDS: Electroactive polymers, Robotics, Sensors, Actuators, Polymers, Artificial intelligence, Machine learning, Computer aided design

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Current robotic sensing is mainly visual, which is useful up until the point of contact. To understand how an object is being gripped, tactile feedback is needed. Human grasp is gentle yet firm, with integrated tactile touch feedback. Ras Labs makes Synthetic Muscle™, which is a class of electroactive polymer (EAP) based materials and actuators that sense pressure from gentle touch to high impact, controllably contract and expand at low voltage (battery levels), and attenuate force. The development of this technology towards sensing has provided for fingertip-like sensors that were able to detect very light pressures down to 0.01 N and even 0.005 N, with a wide pressure range to 25 N and more and with high linearity. By using these soft yet robust Tactile Fingertip™ sensors, immediate feedback was generated at the first point of contact. Because these elastomeric pads provided a soft compliant interface, the first point of contact did not apply excessive force, allowing for gentle object handling and control of the force applied to the object. The Tactile Fingertip could also detect a change in pressure location on its surface, i.e., directional glide provided real time feedback, making it possible to detect and prevent slippage by then adjusting the grip strength. Machine learning (ML) and artificial intelligence (AI) were integrated into these sensors for object identification along with the determination of good grip (position, grip force, no slip, no wobble) for pick-and-place and other applications. Synthetic Muscle™ is also being retrofitted as actuators into a human hand-like biomimetic gripper. The combination of EAP shape-morphing and sensing promises the potential for robotic grippers with human hand-like control and tactile sensing. This is expected to advance robotics, whether it is for agriculture, medical surgery, therapeutic or personal care, or in extreme environments where humans cannot enter, including with contagions that have no cure, as well as for collaborative robotics to allow humans and robots to intuitively work safely and effectively together.

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