A new CNN based path planning algorithm improved by the Doppler effect
Ramazan Yeniçeri, Mustak Erhan Yalcin · 2012
Many path planning and navigation papers using Cellular Neural/Nonlinear Networks (CNN) are found in literature. High proportion of these works originated by wave processing feature of CNN. This paper proposes a special condition of a known Cellular Nonlinear Network model which makes the network very proper to obtain nested and repetitive travelling waves. The Doppler effect appears as a corollary using this special condition. The main contribution of the Doppler effect to the path planning applications that uses CNNs is giving an opportunity to adjust the tracker's speed or change the route completely, dependent to the target's motion. By this way, this paper gains a new qualification to the CNN-based wave computing techniques putting the wave source's motion into use.