SBIR Phase I: Pneumatic Shell Grippers with Highly Tunable Adhesion for Compliant Manipulation

The broader/commercial impact of this Small Business Innovation Research Phase I project is to create a new type of robotic gripper using soft shells. These shell grippers can gently pick up and release small, delicate, and curved items—things that current robots struggle to handle. These items are common in electronics, healthcare, and agriculture, where automation has not worked well due to a lack of suitable grippers. The new shell grippers will use air pressure and have highly tunable adhesion, so they can hold fragile objects without breaking them and let go without sticking. This technology could address labor shortages, speed up production, improve product quality, and make workplaces safer. It will also help turn university research into real products, train skilled workers, and support the U.S. in staying a global leader in robotics and automation. This Small Business Innovation Research Phase I project will significantly advance a soft robotic gripper technology based on the highly tunable adhesion of elastomeric shells toward commercialization. Existing grippers typically struggle to handle small, delicate, and curved objects. This project will develop shell grippers to overcome this limitation using a fundamentally different approach to gripping, which will enable automated manipulation of challenging objects such as those encountered in microelectronics assembly. These soft-shell grippers have the potential for highly tunable dry adhesion (~1000 times) with fast activation time (< 1 second), low activation pressure (~10 kPa), and high resistance to misalignment and surface contamination. Through this project, high risk technical challenges in developing such reliable shell grippers with low-pressure actuation will be addressed through a comprehensive research and development plan. These challenges include the optimization of shell geometry to improve activation speed, the judicious adoption of novel elastomeric composites to remove undesirable electrostatic effects, the characterization of the fatigue performance of the shells over many cycles in various operating environments, and the characterization of shell adhesion against surfaces with different levels of contamination. Successful completion of this project will further develop this soft robotic gripping technology towards real-world commercial products. This foundation will enable future integration of the soft-shell grippers with intelligent software systems that include computer vision and machine learning algorithms for further simplification of human-machine interactions during manipulation tasks. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.