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Zhenhua Pan

Bio: Zhenhua Pan is an academic researcher from Beijing Institute of Technology. The author has contributed to research in topics: Computer science & Obstacle avoidance. The author has an hindex of 4, co-authored 11 publications receiving 27 citations.

Papers
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Journal ArticleDOI
01 Nov 2019-Robotica
TL;DR: An obstacle-avoidance method based on the improved artificial potential field (IAPF) and PID adaptive tracking control algorithm and a series of simulation results confirm that the approaches proposed in this paper can successfully address the obstacle- and collision- avoidance problem while reaching formation.
Abstract: As for the obstacle avoidance and formation control for the multi-robot systems, this paper presents an obstacle-avoidance method based on the improved artificial potential field (IAPF) and PID adaptive tracking control algorithm. In order to analyze the dynamics and kinematics of the robot, the mathematical model of the robot is built. Then we construct the motion situational awareness map (MSAM), which can map the environment information around the robot on the MSAM. Based on the MSAM, the IAPF functions are established. We employ the rotating potential field to solve the local minima and oscillations. As for collisions between robots, we build the repulsive potential function and priority model among the robots. Afterwards, the PID adaptive tracking algorithm is utilized to multi-robot formation control. To demonstrate the validity of the proposed method, a series of simulation results confirm that the approaches proposed in this paper can successfully address the obstacle- and collision-avoidance problem while reaching formation.

23 citations

Journal ArticleDOI
TL;DR: A new underwater obstacle avoidance control algorithm for multi-joint snake-like robots based on the combination of IB-LBM and APF and the best parameters suitable for obstacle avoidance of a robot are found to improve the rapidity and stability of the whole system.
Abstract: In order to study the rapidity and stability of multi-joint snake-like robots in underwater obstacle avoidance, a new underwater obstacle avoidance control algorithm for multi-joint snake-like robots based on the combination of IB-LBM (Immersed Boundary-Lattice Boltzmann Method) and APF (Artificial Potential Field) is proposed in this paper. Firstly, the IB-LBM is used to establish the non-linear flow field model and the fluid-structure coupling model of a multi-joint snake-like robot. Secondly, the 2-D Serpentine curve equation of motions of a multi-joint snake-like robot is improved, and APF method is added to each joint of the robot to control its motion direction, so as to achieve effective obstacle avoidance of the robot in the flow field. Then by MATLAB simulation experiment, influences of different control parameters on obstacle avoidance performance of a multi-joint snake-like robot are analyzed, and the best parameters suitable for obstacle avoidance of a robot are found to improve the rapidity and stability of the whole system. Finally, an underwater obstacle avoidance experiment of a multi-joint snake-like robot is carried out to verify the effectiveness of the proposed control algorithm in real environment.

13 citations

Journal ArticleDOI
TL;DR: An adaptive path following the controller of a multijoint snake robot (MSR) based on the improved Serpenoid curve is proposed, which can make the MSR follow the desired path and make the position error possess fast convergence speed and high stability.
Abstract: An adaptive path following controller of a multi-joint snake robot (MSR) based on the improved Serpenoid curve is proposed. The proposed controller can make the MSR follow the desired path. Compared with the traditional controller, this controller can make the position error possess fast convergence speed and high stability. The swing amplitude in the Serpenoid gait equation is optimized to the time-varying amplitude related to the robot state, enabling the robot to adjust the body swing according to the changes of the environment. Simultaneously, the controller can estimate unknown friction coefficients, which improves the adaptive path following ability of the MSR in an environment with unknown friction coefficients. Firstly, the dynamic model without lateral force is established. Then, the control objectives of the controller are formulated. Thirdly, the Serpenoid gait equation is improved, and the state-dependent time-varying amplitude is obtained. Fourthly, the input-output control function of the system and the tracking function of the swing amplitude compensation are designed by the adaptive control method. The stability of the motion attitude angle variable errors and uniformly ultimately bounded stability of the tracking position are verified, respectively. Finally, the effectiveness and superiority of the proposed controller are verified by experiments.

12 citations

Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper presented a collaborative obstacle avoidance algorithm of multiple bionic snake robots in fluid based on IB-LBM, which can make the multiple snake robots avoid different obstacles in the fluid under the control of the improved Serpenoid curve function.
Abstract: This paper presents a collaborative obstacle avoidance algorithm of multiple bionic snake robots in fluid based on IB-LBM. The method can make the multiple bionic snake robots avoid different obstacles in the fluid under the control of the improved Serpenoid curve function. The proposed method has high parallelism, can simulate the complex non-linear phenomenon of the multiple snake robots, deal with the complex boundary conditions of the robot, and reduce the conversion of the computational grid. Firstly, a non-linear fluid model is established by LBM, which solves the non-linear problem that the classical Navier–Stokes equations cannot explain the random motion. Secondly, the force source boundary model of multiple bionic snake robots is established by IBM, which saves the calculation time, improves the calculation efficiency and system stability. After that, each bionic snake robot is given a special force to make the robots collaborate with each other and non-colliding with each other in the process of the obstacle avoidance. Finally, through simulation experiments, the trajectory of multiple bionic snake robots avoiding different number of the obstacles in the fluid is analyzed and the collaborative obstacle avoidance process of multiple bionic snake robots in fluid is observed. The validity of the collaborative obstacle avoidance algorithm of multiple bionic snake robots in fluid based on the IB-LBM is verified.

9 citations

Journal ArticleDOI
TL;DR: The theoretical analysis and numerical simulation show that the designed trajectory tracking control law can make the multi-joint snake-like robot track the trajectory of the front joint when the robot encounters obstacles and make the robot stabilize the lateral distance, longitudinal distance, and direction angle, so as to effectively avoid obstacles.
Abstract: Aiming at the problem of trajectory tracking between joints of the multi-joint snake-like robot in the flow fields, a trajectory tracking control law proposed based on the improved snake-like curve...

8 citations


Cited by
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Journal ArticleDOI
TL;DR: A review on the snake motion and the body structure is provided, which outlines the biological foundation of all snake robots and the mechanical structure of snake robots, especially the structure of elemental snake modules are discussed.

50 citations

Journal ArticleDOI
TL;DR: Experimental results show that JPSO algorithm has higher accuracy and faster convergence speed than the other two improved PSO algorithms, and SGOA algorithm can solve the dynamic obstacle avoidance problem in the path planning of multiple robots well.

31 citations

Journal ArticleDOI
TL;DR: The k-means method is used to integrate and optimize the attractive force between UAVs, and the concept of virtual core is introduced to realize the cluster control and adaptive formation flight of multiple Uavs.
Abstract: In this paper, a method of multi UAV cluster control based on improved artificial potential field (APF) is proposed. The k-means method is used to integrate and optimize the attractive force between UAVs, and the concept of virtual core is introduced to realize the cluster control and adaptive formation flight of multiple UAVs. The attractive disturbance component of the target point is introduced and the backtracking-filling method is proposed to solve the local minimum problem in the APF. The repulsion force in the APF can realize obstacle avoidance and collision avoidance, and the virtual core can control the UAV cluster to fly to the target point under the attractive force of potential field, so as to realize the track planning and multi aircraft cooperative task. In the process of cluster flight when the UAV fails, merges or dispatches, the method can realize cluster reconfiguration and the cluster control effect and task execution success rate can be improved. The simulation experiments in virtual APF and urban environment APF show the effectiveness of this method.

29 citations

Journal ArticleDOI
TL;DR: A PID controller based on fuzzy neural network algorithm is developed in this paper for tracking the trajectory and contact constant force simultaneously and numerical simulation results are reported to demonstrate the effectiveness of the proposed method.
Abstract: The increased demand for robotic manipulator has driven the development of industrial manufacturing. In particular, the trajectory tracking and contact constant force control of the robotic manipulator for the working environment under contact condition has become popular because of its high precision and quality operation. However, the two factors are opposite, that is to say, to maintain constant force control, it is necessary to make limited adjustment to the trajectory. It is difficult for the traditional PID controller because of the complexity parameters and nonlinear characteristics. In order to overcome this issue, a PID controller based on fuzzy neural network algorithm is developed in this paper for tracking the trajectory and contact constant force simultaneously. Firstly, the kinetic and potential energy is calculated, and the Lagrange function is constructed for a two-link robotic manipulator. Furthermore, a precise dynamic model is built for analyzing. Secondly, fuzzy neural network algorithm is proposed, and two kinds of turning parameters are derived for trajectory tracking and contact constant force control. Finally, numerical simulation results are reported to demonstrate the effectiveness of the proposed method.

17 citations

Journal ArticleDOI
TL;DR: By analyzing the relationship between the forward thrust of the robot and the improved Serpenoid curve equation, a simple, efficient and reliable closed-loop control system was designed and the validity of the motion planning algorithm of a multi-joint snake-like robot based on improvedSerpenoids curve equation is verified by the actual experiment.
Abstract: In order to study the winding motion of a multi-joint snake-like robot with multi-degree of redundancy in plane, a motion planning algorithm of a multi-joint snake-like robot based on improved Serpenoid curve equation is proposed in this paper. Firstly, the kinematics and dynamics models of a multi-joint snake-like robot are established, and the joint angle curve equation and the thrust expression of each joint of the robot relative to time are obtained. Next, the existing Serpenoid curve equation is improved to calculate the axial bending moment function with joint angle amplitude adjustment factor and turn angle adjustment factor. By analyzing the relationship between the forward thrust of the robot and the improved Serpenoid curve equation, a simple, efficient and reliable closed-loop control system was designed. Then, MATLAB and SimWise4D were used for simulation to obtain the motion trajectory of the robot based on the improved Serpenoid curve motion planning algorithm, and the influence of different parameters on the forward velocity of the multi-joint snake robot was analyzed. Finally, the validity of the motion planning algorithm of a multi-joint snake-like robot based on improved Serpenoid curve equation is verified by the actual experiment.

17 citations