Abstract
Pest control robots are one sector in which industries keenly look for various developments. Pesticide diffusion is one of the routine pest-control tasks that can be carried out using autonomous robots. However, the conventional path planning approaches focus on area coverage without considering the optimality in uniform pesticide diffusion and end up in extra consumption of time and energy. This paper presents a novel approach to trajectory planning for pest control robots by exploiting the concept of functional footprint to achieve optimal uniformity in gas diffusion with minimal energy and time. Uniformity number is assigned for the diffusion of pesticide effectiveness(gas) in pest control tasks in zigzag path planning by implementing a nonparametric data approach in Gaussian kernel density estimation and by plotting Contour Kernel density estimation plots and 3-dimensional surface plots for zig-zag path planning trajectory. The uniformity number and time(energy) are optimized by meta-heuristic genetic algorithms NSGAii and AGMOEA to obtain the optimal footprint. To demonstrate the efficacy of the proposed methodology, experimental solutions are evaluated on the Falcon robot, and the parameters are assessed using the results.