Casper: An Assistive Kitchen Robot to Promote Aging in Place1

摘要

A rapidly aging population creates significant issues in maintaining the health and wellbeing of the elderly demographic [1]. Cognitive impairment can progressively diminish a person's memory, orientation, verbal skills, visuospatial ability, abstract reasoning, and attentional skills [2], hence, increasing the need for assistance with everyday activities. In general, this population overwhelmingly prefers to stay in their homes and age-in-place as independently as possible [3]. However, a decline in cognitive abilities may make it difficult to maintain such independence in the comfort of their own homes.In order to facilitate independent living, it is important that older adults be able to perform instrumental activities of daily living (IADLs). Due to the prevalence of malnutrition in elderly individuals, particularly those with cognitive impairments, promoting healthy meal preparation and eating habits is pertinent to maintaining quality of life. To date, even though a number of smart home technologies have been developed to assist the elderly with IADLs, few technologies have been targeted for the kitchen environment.In this paper, we propose the development of a unique assistive kitchen robotic system to enable the elderly with cognitive impairments to independently carry out regular kitchen activities. The Casper robot will assist the users with kitchen activities such as remembering mealtimes, choosing a meal option, remembering the locations of stored items, and assisting step-by-step in the meal preparation process, via the use of speech, facial expressions, and a touchscreen interface.This project addresses the need for an assistive kitchen robotic system for the home that incorporates a cognitive assistance feature to help a user overcome initiation, planning, attention, and memory deficits, while performing regular kitchen activities. The advantage of using the robot is that it is a proactive autonomous system that can find people in the home at mealtimes, escort them to the kitchen, and provide them with assistance in choosing and preparing a meal.The Casper robot, Fig. 1, is a human-like robot consisting of a wheeled omnidirectional mobile base onto which a torso with two arms and a head is placed. The robot's arms (three degrees-of-freedom each), emotive head, and tablet display are used for direct verbal and nonverbal (i.e., greeting and pointing gestures, facial expressions, video, and text instructions) communication. Using a combination of light-emitting diode (LEDs) for both the robot's eyebrows and mouth, Casper can display a standard set of facial expressions (happy, sad, surprised, angry, and neutral) that assist in creating social context during interactions. In Fig. 1, a happy facial expression is displayed. The robot's main processing unit is a mini-PC placed in its base that runs the robot operating system framework [4].The intended assistive scenario (demonstrated here) for the robot consists of the following steps, Fig. 2. First, the robot begins searching the home to locate the user to initiate meal preparation. Once the user is identified, the robot escorts him/her to the kitchen area, and guides him/her through a meal preparation task.Casper utilizes a predictive search strategy to find the user by prioritizing search locations based on patterns of user locations (e.g., kitchen, living room) and behaviors (e.g., meal preparation, leisure activity) in the home environment, Fig. 2. Namely, a hidden Markov model (HMM) is used to define relationships between user locations ot and behaviors xt at time t. This model is then used to predict the user's current location using any observed information on the user's past location (e.g., TV left on in living room).The transition matrix T and emission matrix E for the HMM are trained using maximum-likelihood estimation [5] on data provided by self-reported user schedules. T governs state transitions between neighboring behaviors xt and xt−1, while E determin