Fuzzy PID-inspired Potential Field Path Planning for Quadrotors in Environmental Monitoring

This paper introduces a novel approach for quadrotor path planning referred to as the fuzzy PID-inspired adaptive potential field method (FPID-APFM). Traditional potential field methods (PFMS) face challenges like getting stuck in local minima, oscillating near obstacles, and requiring fine-tuning of parameters. To overcome these problems, the proposed method integrates a fuzzy inference system that dynamically adjusts key parameters, including the attractive force coefficient (ka) and repulsive force coefficient (kb). The idea behind this is inspired by PID controllers, where ka functions similarly to the proportional gain (kp), which helps the quadrotor move toward its goal, and kы functions similarly to the integral gain (k), accounting for the cumulative effects of obstacles and reducing the significant deviations by the quadrotor. A damping factor, ۳, is also included to ensure smoother paths, especially in dynamic conditions. Through simulations in both static and dynamic environments, including scenario with wind disturbances, the results show that the method performs well. This approach proves to be a reliable and efficient solution for real-world path planning, enabling quadrotors to navigate safely while collecting environmental data.

کلیدواژه ها:

Fuzzy Adaptive Potential Field Method ، Quadrotor Path Planning ، Environmental Monitoring ، Fuzzy Logic ، PID Controllers