Title :
RSAW: A situation awareness system for autonomous robots
Author :
Ben Ghezala, Mohamed Walid ; Bouzeghoub, Amel ; Leroux, Christophe
Author_Institution :
LRI, CEA-LIST, Moulon, France
Abstract :
Services and technologies are in evolution in order to develop a new generation of robotic systems that might operate in dynamic real-world environments. In this paper, we focus on the ability of robot to understand and to surpass the blocked situations autonomously without operator intervention. Such situations may occur when the robot cannot succeed the current action and cannot move to the next one. We remark that in the literature, the operator has a crucial role consisting in providing all information about the environment and in making interpretations. In this paper, we propose an RSAW (Robot Situation AWareness) system, developed in order to help a robot to surpass a blocked situation and accomplish its goal whilst minimizing the operator intervention. RSAW is a new general system aiming to increase the autonomy of the robot; It is inspired by the notion of Situation Awareness (SA). In fact, RSAW defines a knowledge representation using ontologies and a process in order to surpass a blocked situation. RSAW is designed according to the Model Driven Engineering (MDE) methodology. This choice is done to preserve the generality of our system. This paper focalizes on the process of the RSAW system and the interaction between the process and the knowledge representation. The experimentations conducted in real environment with the Smart Autonomous Majordomo (SAM) robot, have shown the robustness and the efficiency of the proposed system.
Keywords :
control engineering computing; mobile robots; ontologies (artificial intelligence); robot dynamics; robust control; software engineering; MDE methodology; RSAW; SAM robot; autonomous robots; dynamic real-world environment; knowledge representation; model driven engineering methodology; ontology; operator intervention; robot situation awareness system; robotic system; robustness; smart autonomous majordomo robot; Ontologies; Predictive models; Resource description framework; Robot sensing systems; Semantics;
Conference_Titel :
Control Automation Robotics & Vision (ICARCV), 2014 13th International Conference on
DOI :
10.1109/ICARCV.2014.7064347