SBIR Phase I: Gentle: A Smart, Affordable, Soft Gripper for Robotic Food Picking and Packaging

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the improvement in throughput of fresh fruit, vegetable, baked item picking and packing, agriculture, and tasks that require physically handling or grasping a wide range of delicate objects. The electrically-actuated soft robotic gripper technology is inherently safe to work in human-occupied environments and collaborate with human workers since its soft fingers can deform and absorb impacts in case of a collision.

In addition, with the data generated from the research and development, new use cases will be opened for robotic hands in the long term such as helping farmers pick fruits from trees. Working in the robotics technology area and targeting items that are difficult to pick up by traditional robotic grippers and algorithms, the research will help automate and increase the efficiency of traditionally manual processes that suffer from a lack of enough workers to ultimately support American manufacturing.

This research also has longer-term benefits to expand into other sectors such as collaborative robotics, healthcare, and assistive robotics areas because of the inherent safety and adaptability of soft robotics in human interaction.

This Small Business Innovation Research (SBIR) Phase I project focuses on technical research and development of electrically actuated soft grippers with a modular approach, sensory integration, and feedback control, as well as the study of new algorithms and user interfaces to endow these systems with intelligence for improved performance. When there is variation in object size, weight, shape, and fragility, robotic system integrators find it difficult to use traditional rigid and expensive grippers to automate mundane, low-value tasks.

Soft grippers can provide a solution, adapting to variations in objects and other conditions. Enabling electrical operation of soft fingers enables direct integration with robotic arms eliminating complex infrastructure requirements and reducing cost, which will help improve the return on investment and reduce barriers of entry for small businesses to utilize this latest technology.

The research will undertake testing and validation under common, realistic conditions encountered in fresh produce picking and packing and e-commerce order fulfillment applications. The research goals are to: optimize the design and fabrication techniques and quantify grasping behavior for improved adaptability, provide feedback control, and integrate intelligence to the grippers by incorporating data and user input to determine optimal grasp parameters.

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.