ShelfHelp: Empowering Humans to Perform Vision-Independent Manipulation Tasks with a Socially Assistive Robotic Cane
Shivendra Agrawal, Suresh Nayak, Ashutosh Naik, and Bradley Hayes

TL;DR
ShelfHelp is a novel socially assistive robotic system that helps visually impaired individuals locate and retrieve products in grocery stores using an instrumented cane with visual and verbal guidance capabilities.
Contribution
The paper introduces a new robotic cane system with a visual product locator and autonomous verbal guidance, advancing assistive technology for shopping independence.
Findings
System successfully locates products in grocery settings.
Verbal guidance modes perform comparably to human assistance.
Participants report high ease of use and perceived competence.
Abstract
The ability to shop independently, especially in grocery stores, is important for maintaining a high quality of life. This can be particularly challenging for people with visual impairments (PVI). Stores carry thousands of products, with approximately 30,000 new products introduced each year in the US market alone, presenting a challenge even for modern computer vision solutions. Through this work, we present a proof-of-concept socially assistive robotic system we call ShelfHelp, and propose novel technical solutions for enhancing instrumented canes traditionally meant for navigation tasks with additional capability within the domain of shopping. ShelfHelp includes a novel visual product locator algorithm designed for use in grocery stores and a novel planner that autonomously issues verbal manipulation guidance commands to guide the user during product retrieval. Through a human…
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