Welcome to the InfoSci Platform
Reference Hub1
Optimal Robot Path Planning with Cellular Neural Network

Optimal Robot Path Planning with Cellular Neural Network

Yongmin Zhong, Bijan Shirinzadeh, Xiaobu Yuan
Copyright: © 2011 |Volume: 1 |Issue: 1 |Pages: 20
ISSN: 2156-1664|EISSN: 2156-1656|EISBN13: 9781613507971|DOI: 10.4018/ijimr.2011010102
Cite Article Cite Article

MLA

Zhong, Yongmin, et al. "Optimal Robot Path Planning with Cellular Neural Network." IJIMR vol.1, no.1 2011: pp.20-39. http://doi.org/10.4018/ijimr.2011010102

APA

Zhong, Y., Shirinzadeh, B., & Yuan, X. (2011). Optimal Robot Path Planning with Cellular Neural Network. International Journal of Intelligent Mechatronics and Robotics (IJIMR), 1(1), 20-39. http://doi.org/10.4018/ijimr.2011010102

Chicago

Zhong, Yongmin, Bijan Shirinzadeh, and Xiaobu Yuan. "Optimal Robot Path Planning with Cellular Neural Network," International Journal of Intelligent Mechatronics and Robotics (IJIMR) 1, no.1: 20-39. http://doi.org/10.4018/ijimr.2011010102

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

This paper presents a new methodology based on neural dynamics for optimal robot path planning by drawing an analogy between cellular neural network (CNN) and path planning of mobile robots. The target activity is treated as an energy source injected into the neural system and is propagated through the local connectivity of cells in the state space by neural dynamics. By formulating the local connectivity of cells as the local interaction of harmonic functions, an improved CNN model is established to propagate the target activity within the state space in the manner of physical heat conduction, which guarantees that the target and obstacles remain at the peak and the bottom of the activity landscape of the neural network. The proposed methodology cannot only generate real-time, smooth, optimal, and collision-free paths without any prior knowledge of the dynamic environment, but it can also easily respond to the real-time changes in dynamic environments. Further, the proposed methodology is parameter-independent and has an appropriate physical meaning.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.