## 1 Introduction
### Scope
Specifically, 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. Moreover, the robot did not have situation awareness about the success of its task, while it was not able to return the medication back to its storage position. Contrary to the above-mentioned methodology, this paper deals with the entire pipeline of robotic medication assistance. The proposed system, not only offers solutions to all the aforementioned challenges, but turns the robot into an active agent responsible for delivering the medication to the user and drawing a conclusion regarding the outcome of its mission, being able to answer with a certain confidence on the question: _\"Has the user received the medication?\"_ instead of treating the robot as a fetching device responsible only for delivering the medication container to the user. In order to achieve this, a mobile robot manipulator equipped with vision sensors has been utilized. Vision-based object detection and grasping from demanding spots have been developed in order to reach the medication box from challenging places, while the entire fetching task of medication has been implemented in a modular and dependable manner. Moreover, efficient human detection and tracking methodologies have been adopted to robustly apprehend the human presence in the environment and reach him/her with safety, while a dedicated solution to monitor the medication adherence action has been developed. The robot cognitive ability that enablesthe denouement of medication assistance scenario has been realised through a Partially observable Markov decision process (POMDP) model that can handle the uncertainty of the perception input and promptly decide on the next best robot action. The decision maker interacts directly with a robot task planner which is capable of orchestrating the robot skills, along with the communication modalities that have been developed, covering the multiple aspects of the medication assistance scenario and thus offering a fully autonomous solution. To the best of our knowledge, this is the first working solution that addresses the complete pipeline for the medication assistance task involving autonomy, perception, cognition, human action monitoring and task planning. It is important to state herein that the ultimate goal of this paper is to provide solutions in a series of perception, cognition and action problems that will enable, in the near future, assistive robots' deployment in real home environments. The main novelty and contributions of this work are summarized as follows:  
* The development of an integrated vision system able to perform object and human detection and tracking suitable for monitoring of medication activities;
* The integration of novel object grasping strategies with environmental contact, enabling object manipulation from challenging spots accompanied with situation awareness mechanisms;
* The development of safe manipulation and navigation strategies suitable for robotic agents that target operation in domestic environments with non-expert robot users;
* The identification of the necessitated robot skills for assistance in medication adherence activity, their development in a modular manner and their organization under a task planner framework that covers all the corner cases that can be identified within the examined assistive scenario;
* The integration and assessment of all the developed skills in multiple realistic scenarios with various users.