SBIR Phase I: Haptic Robotics for Kitting Powertrain Components

This Small Business Innovation Research (SBIR) Phase I project proposes that haptic robots offer effective and attractive solutions to the common tasks of Bin-Picking and Kitting, which currently require human workers. A popular application area is programming an industrial robot to work with specific powertrain parts. The Problem: Bin-picking robots can only manipulate strong parts with simple geometries in structured or semistructured configurations; machine vision deals poorly with overlapping objects and unstable and unpredictable loads or grips. The Opportunity: Haptic systems can compliment machine vision systems using tactile sensory data to cope with overlapping objects and unstable grip conditions. The Solution: A robotic hand/arm equipped with unique biomimetic tactile sensors to make a platform for developing grip algorithms for parts picking and kitting. Innovations include develop algorithms for slip-detection and force-cone grip adjustment; developing adaptive algorithms using tactile feedback to improve grip pre-shaping; validating algorithms with physical powertrain parts; and challenging algorithms with real-world uncertainties that are difficult to detect using machine vision. The broader impact/commercial potential of this project will result in robots that have more humanlike haptic capabilities. Currently robots lack tactile sensing and rely on specialized component feeders and gripping tools to handle individual objects with predetermined gripping features. These items add cost, occupy space, and consume time, especially when many different objects must be handled. This puts robots at a significant disadvantage to human workers who use their hands dexterously to handle an unlimited variety of objects. Nevertheless, robots are best suited to handle tasks that are highly repetitive or dangerous to humans. When robots handle hazardous materials or manufacturing tasks, they relieve humans of these burdens while often yielding increased productivity and cost-savings. At the end of Phase I we will have developed a proof of concept so that our Phase II research can integrate the system into an industrial environment. By addressing the picking of objects with errors in object pose, position and part-to-part interaction, haptic robots will transform this important part of the manufacturing process. Such technology will have widespread impact on many aspects of manufacturing and automation.