Knowledge-enabled decision making for robotic system utilizing ambient service components

Abstract

Robotic and ambient intelligent environments are much more demanding regarding the knowledge a robot needs to have. A skilled robot performs human-scale manipulation tasks, interacts with a variety of objects, understands instructions given by humans and most importantly, requires the capability of interpreting ubiquitous resources and assembling them into a complex plan. In this paper, a novel Knowledge-enable Decision Making Framework (KDMF) is proposed for Component-Based Robotic System (CBRS). We exploit that the use of domain knowledge is pivotal to endow robots with higher degrees of autonomy and intelligence in CBRS. Ontology knowledge about classes, properties, relations is organized in OWL based conceptual map, which allows automated inference to derive new pieces of information. Knowledge about tasks is specified in a tree data structure, and knowledge about components' functions is formulated by a specific type of service specification profile. Using the knowledge representation, a task-oriented decision making method is proposed that integrates knowledge inference and service components utilization. In practical applications of ambient and robotic assisted living, robot's plans generated by the decision making software are based on the knowledge of components, rather than particular device instances, which improves the reusability and flexibility of the system. Experimental results validate the effectiveness of the proposed method.

Bath-Ambience—A Mechatronic System for Assisting the Caregivers of Bedridden People

“…It is important to mention that this project represents a technical innovation inside the Ambient Assisted Living (AAL) paradigm, offering and increasing opportunities for an independent and self-determined way of life for older people living at home or in care facilities [ 9 , 10 , 11 ].…”

“…Environment variables can also be monitored by the system [ 14 ]. The environment for giving an automated bath was developed to meet the different demands of patients; therefore, it provides an environment that supports the patient in standing in a vertical position, which makes it possible to run a pre-programmed course of a sequence of tasks: lathering, rinsing and drying, in order to minimize the effort of caregivers [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ].…”

“…Therefore, the need to have a healthy ageing society requires major help from technology [ 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 ]. Considering technologies developed to assist the activities to care for bedridden people, there have been several developments in the bathing area, such as improving the the environment for giving the bath, smart bathrooms [ 5 , 6 , 7 , 8 ], bed technology [ 14 , 15 ], washing systems [ 16 , 17 , 18 , 19 ], including the use of body sensors and control systems [ 20 , 21 , 22 , 23 , 24 ].…”

A Utilization Framework of Ubiquitous Resources for Service Robots Using Semantic Matchmaking

“…Correspondingly, the exit of the maze is also simulated by a virtual node S RO or S RE . The matching proceeds according to the Qualified Pre-action /pre-service criteria and the Qualified Post-action /post-service criteria, as defined in [30].…”