📑 Shivendra's work on assisting visually impaired people to perform independent grocery shopping accepted at AAMAS 2023!

In this work, an end-to-end system is described that can locate grocery items using a novel 2-stage computer vision pipeline and provide fine-grain assitive manipulation guidance to retrieve it. The work also presents a comparitive study with a baseline system, and a human guide.

ShelfHelp: Empowering Humans to Perform Vision-Independent Manipulation Tasks with a Socially Assistive Robotic Cane

Shivendra Agrawal, Suresh Nayak, Ashutosh Naik, and Bradley Hayes


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.

The paper can be accessed here, and from our Publications tab.

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