Towards Assistive Robotic Pick and Place in Open World Environments
This work addresses the need for more capable and user-friendly assistive robotic systems for individuals with mobility impairments, though it is incremental as it builds on existing methods.
The paper tackles the problem of enabling assistive robots to autonomously pick and place novel objects in open-world environments without modeling objects or the environment, resulting in significant improvements in runtime and grasp success rate compared to a baseline.
Assistive robot manipulators must be able to autonomously pick and place a wide range of novel objects to be truly useful. However, current assistive robots lack this capability. Additionally, assistive systems need to have an interface that is easy to learn, to use, and to understand. This paper takes a step forward in this direction. We present a robot system comprised of a robotic arm and a mobility scooter that provides both pick-and-drop and pick-and-place functionality for open world environments without modeling the objects or environment. The system uses a laser pointer to directly select an object in the world, with feedback to the user via projecting an interface into the world. Our evaluation over several experimental scenarios shows a significant improvement in both runtime and grasp success rate relative to a baseline from the literature [5], and furthermore demonstrates accurate pick and place capabilities for tabletop scenarios.