Smart Grasping

With iGrasp, we answer the question: what sensor technologies can we use that would improve the performance of our robot Hand for grasping? An optimal number of low-cost tactile and proximity sensors are integrated with the fingertips of our new Hand to enhance the reliability of the prototype and expanding the grasping capabilities for a wide range of objects. The system keeps on learning the best way to grasp different objects; starting from a good grasp configuration and refining it autonomously each time an object is grasped. The goal achieved is to grasp any object with a simple high-level command so that it can be used in industry and by people who are not experts in robotic grasping.

Date: 2018-2019

Funded by: Innovate UK (Ref: 103676)

Partners: Shadow Robot Company (SRC), Queen Mary University of London (QMUL)