## 1 Introduction  
### Scope  
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. Recently, significant steps have been made in the context of service robotics for assisted living environments to support older people's independence [1]. In accordance with a recent literature review, provided by [PERSON] et al. (2015), up to 2015, more than 100 assistive robots have been developed aiming to support a wide range of different activities of elderly people among which mobility, self-care, social, and others of general purpose related activities can be identified. 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 medication-adherence, in order to be able to live independently [2]. However, management of complex medication regimens by the elderly poses a significant challenge. This may stem from diverse reasons, ranging from the complexity of the medication schedule, when combined with the declining cognitive capacities of the users, to the human's forgetfulness and apathy [3]. Personal assistive robots can assist older adults with managing their medication activities; however, there are significant barriers that need to be surpassed in order to realize a complete solution in the domain of medication assistance that will allow cross-environment applicability, repeatability and robustness. Specifically, 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. The robot should have the capacity to locate the human in the house, while at the same time should be able to apprehend the human's actions related to medication adherence and clearly deduce about the outcome of the interaction. In addition, the robot should be able to administer the medication to the user if s/he will not do it on his/her own, as described by [PERSON] [5], yet respecting the fact that, in healthcare, the patients are not forced to take the medicine they do not want to (with some obvious exceptions). The closest to our work is the one described in [6]. This work is the first attempt that aims to provide a medication assistance by offering intervention in the medication adherence activity with robotic manipulations instead of notifications provision and guidelines, thus addressing the medication fetching task. More specifically, the robot had the capacity to locate the medication in the environment, navigate towards it, grasp it, and then locate the human in the environment, navigate towards him/her and hand-off the medication. However, instead of vision, the perception system of the robot, related to the detection of the medication container and the detection of the participant, has been replaced by a radio frequency identification (RFID) framework where tags are affixed on objects, locations and humans. By placing ultra high frequency (UHF) RFID tags on important objects in an environment, the robot utilized each tag's unique identifier (ID) and signal strength from each tag (RSSI) to detect and localize objects. The medication delivery task performed by commanding the robot to retrieve a tagged medication and deliver it to a user wearing a tag. Upon successful hand-off of the medication, the robot task was completed. It is evident that this approximation was a simplified approach and had certain limitations.