The paper "Dynamic Motion Planning for Mobile Robots Using Potential Field Method" by S.S. GE and Y.J. CUI addresses the challenge of motion planning for autonomous mobile robots in dynamic environments where both the target and obstacles are moving. The authors propose a novel potential field method that incorporates the relative position and velocity of the target and obstacles to enhance the robot's ability to track the target while avoiding moving obstacles. The key contributions include: 1. **New Potential Functions**: The attractive potential function is defined as a function of the relative position and velocity of the target with respect to the robot, and the repulsive potential function is defined as the relative position and velocity of the robot with respect to the obstacles. This allows the robot to track the target more effectively and avoid collisions. 2. **Virtual Force**: The virtual force is defined as the negative gradient of the potential function, considering both position and velocity, rather than just position. This approach ensures that the robot can handle dynamic environments more robustly. 3. **Local Minima Issues**: The paper discusses the problem of local minima, which can occur in the potential field method, and proposes solutions to address this issue. 4. **Experiments**: Extensive computer simulations and hardware experiments are conducted to demonstrate the effectiveness of the proposed dynamic motion planning scheme. The paper is structured into several sections, including an introduction, problem statement, detailed descriptions of the attractive and repulsive potential functions, discussion of local minima, and experimental results. The authors aim to provide a more realistic and practical approach to motion planning for mobile robots in dynamic environments, addressing the limitations of existing methods that often assume stationary targets and obstacles.The paper "Dynamic Motion Planning for Mobile Robots Using Potential Field Method" by S.S. GE and Y.J. CUI addresses the challenge of motion planning for autonomous mobile robots in dynamic environments where both the target and obstacles are moving. The authors propose a novel potential field method that incorporates the relative position and velocity of the target and obstacles to enhance the robot's ability to track the target while avoiding moving obstacles. The key contributions include: 1. **New Potential Functions**: The attractive potential function is defined as a function of the relative position and velocity of the target with respect to the robot, and the repulsive potential function is defined as the relative position and velocity of the robot with respect to the obstacles. This allows the robot to track the target more effectively and avoid collisions. 2. **Virtual Force**: The virtual force is defined as the negative gradient of the potential function, considering both position and velocity, rather than just position. This approach ensures that the robot can handle dynamic environments more robustly. 3. **Local Minima Issues**: The paper discusses the problem of local minima, which can occur in the potential field method, and proposes solutions to address this issue. 4. **Experiments**: Extensive computer simulations and hardware experiments are conducted to demonstrate the effectiveness of the proposed dynamic motion planning scheme. The paper is structured into several sections, including an introduction, problem statement, detailed descriptions of the attractive and repulsive potential functions, discussion of local minima, and experimental results. The authors aim to provide a more realistic and practical approach to motion planning for mobile robots in dynamic environments, addressing the limitations of existing methods that often assume stationary targets and obstacles.