  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 subjects study, we show the
system's success in locating and providing effective manipulation guidance to
retrieve desired products with novice users. We compare two autonomous verbal
guidance modes achieving comparable performance to a human assistance baseline
and present encouraging findings that validate our system's efficiency and
effectiveness and through positive subjective metrics including competence,
intelligence, and ease of use.
