Path Optimization and Obstacle Avoidance using Gradient Method with Potential Fields for Mobile Robot

Research on obstacle avoidance algorithm for wheeled robot based on Raspberry Pi

“…Liu et al [4] proposed an improved artistic potential field local object avoidance path planning algorithm on the Prescan CarSim Matlab/Simulink joint simulation platform. Dubey et al [11] proposed a path optimization and obstacle avoidance approach based on the gradient method with potential fields. Abdallaoui et al [12] carried on a study to identifies the difficulties that recent mobile robot path planning techniques have encountered, such as accurately considering forces and ensuring collision-free navigation.…”

Z-Number-Based Fuzzy Logic Approach for Mobile Robot Navigation

“…However, these methods also face real-world challenges, such as navigating through cluttered environments with movable obstacles [8], avoiding static obstacles [9], and addressing sensing performance issues when using depth cameras and Lidar for navigation [10]. Additionally, Dubey et al [11] proposed a path optimization and obstacle avoidance approach based on the gradient method with potential fields. They developed a segmented structure for independent navigation using deep reinforcement learning via ROS2.…”

“…τ = I * α(10) The dynamics equations for the TurtleBot3 mobile robot can be derived as follows: a) LINEAR DYNAMICS Using Newton's second law of motion, the sum of forces in the x-direction equals the robot's mass times its linear acceleration.𝐹𝑙 + 𝐹𝑟 = 𝑚. 𝑎(11) Since the robot is in a pure rolling motion, the linear acceleration 𝑎 can be expressed in terms of the radius 𝑅 and angular acceleration 𝛼 as 𝑎 = 𝑅. 𝛼 𝐹𝑙 + 𝐹𝑟 = 𝑚.𝑅. 𝛼 (12)b) ANGULAR DYNAMICSThe angular acceleration 𝛼 is related to the torque and moment of inertia: velocities: the wheel velocities (ν𝑙 and ν𝑟) can be related to the linear and angular velocities: between Forces and Torques: The forces 𝐹𝑙 and 𝐹𝑟 can be related to the torques 𝑇𝑙 and 𝑇𝑟 using the radius 𝑅 and wheel radius 𝑟 as follows:…”