http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Xinpeng Zhai (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
-
Xinpeng Zhai,Jianyan Tian,Jifu Li 제어·로봇·시스템학회 2024 International Journal of Control, Automation, and Vol.22 No.4
The fusion of the A* and the dynamic windowing algorithm is commonly used for the path planning of mobile robots in dynamic environments. However, the planned path has the problems of redundancy and low security. This paper proposes a path planning algorithm based on the safety distance matrix and adaptive weight adjustment strategy to address the above problems. Firstly, the safety distance matrix and new heuristic function are added to the traditional A* algorithm to improve the safety of global path. Secondly, the weight of the evaluation sub-function in the dynamic window algorithm is adjusted through an adaptive weight adjustment strategy to solve the problem of path redundancy. Then, the above two improved algorithms are fused to make the mobile robot have dynamic obstacle avoidance capability by constructing a new global path evaluation function. Finally, simulations are performed on grid maps, and the fusion algorithm is applied to the actual mobile robot path planning based on the ROS. Simulation and experimental results show that the fusion algorithm achieves optimization of path safety and length, enabling the robot to reach the end point safely with real-time dynamic obstacle avoidance capability.
-
Ruoyu Xu,Jianyan Tian,Jifu Li,Xinpeng Zhai 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.10
To ensure the smooth operation of each joint and shorten the joint movement time of a rail inspection robot, a trajectory planning method based on time optimization with a penalty function is proposed. According to the Denavit-Hartenberg (D-H) model of the inspection robot, a kinematic solution is found, and the trajectory of each joint is generated using a mixed polynomial interpolation algorithm. Taking time optimization as the standard, the traditional particle swarm algorithm cannot handle complex constraints, easily falls to local optimum solutions, and has a slow convergence speed. An improved simulated annealing particle swarm algorithm with a penalty function (IPF-SA-PSO) is proposed to optimize the trajectory generated by the mixed polynomial interpolation algorithm. The simulation results show that the proposed algorithm, compared with the mixed polynomial interpolation method, can limit the angular velocity and reduce the running time of each manipulator joint. The two algorithms are experimentally verified based on a rail inspection robot, and the results show that after adopting the optimization algorithm, the angular velocity of each joint is within the angular velocity limit, the run time is shorter, and the operation is smoother, which indicates the effectiveness of the proposed algorithm. The proposed algorithm can optimize the robot running time, improve the smoothness, and be applied to the fields of the automatic tracking of abnormal targets and video acquisition.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
