Genetic algorithms for autonomous robot navigation
Engineers and scientists use instrumentation and measurement equipment to obtain information for specific environments, such as temperature and pressure. This task can be performed manually using portable gauges. However, there are many instances in which this approach may be impractical; when gathe...
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| Veröffentlicht in: | IEEE instrumentation & measurement magazine 2007-12, Vol.10 (6), p.26-31 |
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| creator | Manikas, T.W. Ashenayi, K. Wainwright, R.L. |
| description | Engineers and scientists use instrumentation and measurement equipment to obtain information for specific environments, such as temperature and pressure. This task can be performed manually using portable gauges. However, there are many instances in which this approach may be impractical; when gathering data from remote sites or from potentially hostile environments. In these applications, autonomous navigation methods allow a mobile robot to explore an environment independent of human presence or intervention. The mobile robot contains the measurement device and records the data then either transmits it or brings it back to the operator. Sensors are required for the robot to detect obstacles in the navigation environment, and machine intelligence is required for the robot to plan a path around these obstacles. The use of genetic algorithms is an example of machine intelligence applications to modern robot navigation. Genetic algorithms are heuristic optimization methods, which have mechanisms analogous to biological evolution. This article provides initial insight of autonomous navigation for mobile robots, a description of the sensors used to detect obstacles and a description of the genetic algorithms used for path planning. |
| doi_str_mv | 10.1109/MIM.2007.4428579 |
| format | Magazinearticle |
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This task can be performed manually using portable gauges. However, there are many instances in which this approach may be impractical; when gathering data from remote sites or from potentially hostile environments. In these applications, autonomous navigation methods allow a mobile robot to explore an environment independent of human presence or intervention. The mobile robot contains the measurement device and records the data then either transmits it or brings it back to the operator. Sensors are required for the robot to detect obstacles in the navigation environment, and machine intelligence is required for the robot to plan a path around these obstacles. The use of genetic algorithms is an example of machine intelligence applications to modern robot navigation. Genetic algorithms are heuristic optimization methods, which have mechanisms analogous to biological evolution. 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This task can be performed manually using portable gauges. However, there are many instances in which this approach may be impractical; when gathering data from remote sites or from potentially hostile environments. In these applications, autonomous navigation methods allow a mobile robot to explore an environment independent of human presence or intervention. The mobile robot contains the measurement device and records the data then either transmits it or brings it back to the operator. Sensors are required for the robot to detect obstacles in the navigation environment, and machine intelligence is required for the robot to plan a path around these obstacles. The use of genetic algorithms is an example of machine intelligence applications to modern robot navigation. Genetic algorithms are heuristic optimization methods, which have mechanisms analogous to biological evolution. 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| source | IEEE Electronic Library (IEL) |
| subjects | Applied sciences Autonomous navigation Computer science control theory systems Control theory. Systems Exact sciences and technology General equipment and techniques Genetic algorithms Humans Instrumentation Instrumentation and measurement Instruments, apparatus, components and techniques common to several branches of physics and astronomy Intelligence Intelligent robots Intelligent sensors Machine intelligence Mobile robots Navigation Obstacles Physics Robot sensing systems Robotics Robots Sensors Servo and control equipment robots Studies Temperature |
| title | Genetic algorithms for autonomous robot navigation |
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