Safe and effective navigation of autonomous robots in hazardous environments.

Seward, D.W. and Agate, R. and Pace, C. (2007) Safe and effective navigation of autonomous robots in hazardous environments. Autonomous Robots, 22 (3). pp. 223-242. ISSN 1573-7527

Full text not available from this repository.


The development of autonomous mobile machines to perform useful tasks in real work environments is currently being impeded by concerns over effectiveness, commercial viability and, above all, safety. This paper introduces a case study of a robotic excavator to explore a series of issues around system development, navigation in unstructured environments, autonomous decision making and changing the behaviour of autonomous machines to suit the prevailing demands of users. The adoption of the Real-Time Control Systems (RCS) architecture (Albus, 1991) is proposed as a universal framework for the development of intelligent systems. In addition it is explained how the use of Partially Observable Markov Decision Processes (POMDP) (Kaelbling et al., 1998) can form the basis of decision making in the face of uncertainty and how the technique can be effectively incorporated into the RCS architecture. Particular emphasis is placed on ensuring that the resulting behaviour is both task effective and adequately safe, and it is recognised that these two objectives may be in opposition and that the desired relative balance between them may change. The concept of an autonomous system having “values” is introduced through the use of utility theory. Limited simulation results of experiments are reported which demonstrate that these techniques can create intelligent systems capable of modifying their behaviour to exhibit either ‘safety conscious’ or ‘task achieving’ personalities.

Item Type:
Journal Article
Journal or Publication Title:
Autonomous Robots
Additional Information:
This is a recent invited paper for a special edition on construction robotics. It engages with the problem of making autonomous robots, that operate in unstructured environments, both safe and task-effective. The work presented follows correspondence with James Albus of the U.S. National Inst. of Standards and Technology, and the collaboration extends his pioneering work on intelligent system architectures by adding a probabilistic dimension to the interpretation of complex world sensor data ' i.e. safe decision making in the face of incomplete and uncertain information. RAE_import_type : Journal article RAE_uoa_type : General Engineering
Uncontrolled Keywords:
ID Code:
Deposited By:
Deposited On:
27 Mar 2008 09:55
Last Modified:
18 Sep 2023 00:12