Earticle

초록

영어

The ability to adapt automated guided vehicles for employment to a range of practical situations can significantly enhance their usability in hazardous situations where security is a major concern and it is inadvisable for humans to enter. Robot guidance is still a very challenging issue computationally in both the academic and industrial worlds. Whilst considerable progress has been made in robotics in the last few decades, many still experience difficulties in the recognition of dynamically changing situations such as our daily environments. With so many different scenarios it is difficult to find one system that can effectively deal with both the expected and unexpected issues that may arise. This paper examines the possibility of manipulating the potential inputs and outputs to a system to tailor a better solution to the current problem. Weightless neural networks will be used as a classification tool to determine the direction of a robot in an open loop simulation.

목차

Abstract
 1. Introduction
 2. Ultrasonic Sensors
 3. Weightless Networks
 4. The Input
 5. Meta Network Design
  5.1. Inputs
  5.2. Initial Population
  5.3. Crossover
  5.4. Mutation
  5.5. Modifying Inputs and Outputs
 6. Experimentation
 7. Results
 8. Conclusion
 References

키워드

저자

• Ben McElroy [ School of Engineering and Digital Arts, University of Kent ]
• Gareth Howells [ School of Engineering and Digital Arts, University of Kent ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605