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Paper WeC07.2

Gspandl, Stephan (Institute for Software Technology, Graz University of Technology), Podesser, Siegfried (Institute for Software Technology, Graz University of Technology), Reip, Michael (Graz University of Technology), Steinbauer, Gerald (Graz University of Technology), Wolfram, Máté (Science Fund (FWF) by grant P22690. The authors are with the Ins)

A Dependable Perception-Decision-Execution Cycle for Autonomous Robots

Scheduled for presentation during the Regular Session "Environment Mapping" (WeC07), Wednesday, May 16, 2012, 14:45−15:00, Meeting Room 7 (Remnicha)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on October 24, 2017

Keywords Failure Detection and Recovery, AI Reasoning Methods, Autonomous Agents

Abstract

The tasks robots are employed to achieve are becoming increasingly complex, demanding for dependable operation, especially if robots and humans share common space. Unfortunately, for these robots non-determinism is a severe challenge. Malfunctioning hardware, inaccurate sensors, exogenous events and incomplete knowledge lead to inconsistencies in the robot’s belief about the world. Thus, a robot has to cope efficiently with such adversities while sensing its surroundings, deciding what to do next, and executing its decisions. In this paper, we present such a dependable perception-decision-execution cycle. It employs a belief management system that performs history-based diagnosis in the high-level control module. The belief management enables robots to detect these inconsistencies and thus operate successfully in non-deterministic environments. The main contributions of this paper are a robot design extending the high-level control IndiGolog by a belief management allowing to deal with a large variety of faults in a unique way, together with an evaluation on a real robot system.

 

 

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