Abstract
During the last few decades, great research endeavors have been applied to healthcare robots, aiming to develop companions that extend the independent living of elderly people. To deploy such robots into the market, it is expected that certain applications should be addressed with repeatability and robustness. Such application is the assistance with medication-related activity, a common need for the majority of elderly people, referred from here on as medication adherence. This paper presents a novel and complete pipeline for assistance provision in monitoring and serving of medication, using a mobile manipulator embedded with action, perception and cognition skills. The challenges tackled in this work comprise, among others, that the robot locates the medication box placed in challenging spots by applying vision based strategies, thus enabling robust grasping. The grasping is performed with strategies that allow environmental contact, accommodated by the manipulator’s admittance controller which offers compliance behavior during interaction with the environment. Robot navigation is applied for the medication delivery, which, combined with active vision methods, enables the automatic selection of parking positions, allowing efficient interaction and monitoring of medication intake activity. The robot skills are orchestrated by a partially observable Markov decision process mechanism which is coupled with a task planner. This enables assistance scenario guidance and offers repeatability as well as gentle degradation of the system upon a failure, thus avoiding uncomfortable situations during human–robot interaction. Experiments have been conducted on the full pipeline, including robot’s deployment in 12 real house environments with real participants that led to very promising results with valuable findings for similar future applications.
Highlights
In order to reach Pregrasp State (PGS), we command the arm with a wrench FGcmd, which is the sum of two components: one force opposite to the surface normal, which results in an arm motion downward for establishing contact, and one external wrench induced by the contact forces applied by the fingertips to the environment, required for the proper translation and rotation of the hand, so that a full contact with the three fingers is established
Summarizing the paper at hand significantly contributes to the current state-of-the-art solutions for the existing personal assistive robots
It focuses on the verified use case of assistance provision in medication adherence activities and, contrary to the existing works that address the issue of medication adherence partially, the proposed framework outlined a complete pipeline of software operating on hardware that addresses the problem of assistance provision in medication adherence activities fully
Summary
The societal challenge inherent in the growing elderly population is a worldwide phenomenon, which is getting worse when considering that such groups usually suffer from chronic diseases that gradually deteriorate their health status decreasing their physical and mental capabilities. Considering assistance provision to self-care related activities, support in medication adherence is located at the forefront of the contemporary assistive robots’ priorities This falls under the wider requirement for elderly people to maintain their medicationadherence, in order to be able to live independently [2]. The assistive robot should be aware of the medication schedule of the user which may involve multiple sessions within the same day [4] The latter necessitates the ability of the robot to keep track of the objects’ states involved in the medication task (e.g., medication container) within the environment. It is evident that this approximation was a simplified approach and had certain limitations It necessitated intervention in the environment with RFID tags, while it partially tackled the medication assistance considering that monitoring of medication adherence activity was not supported. The integration and assessment of all the developed skills in multiple realistic scenarios with various users
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