Papers by Keyword: Path Planning

Abstract: The ability of a mobile robot to plan its path is the key task in the field of robotics, which is to find a shortest, collision free, optimal path in the various scenes. In this paper, different existing path planning methods are presented, and classified as: geometric construction method, artificial intelligent path planning method, grid method, and artificial potential field method. This paper briefly introduces the basic ideas of the four methods and compares them. Some challenging topics are presented based on the reviewed papers.

Abstract: The artificial potential field method has been extensively used in mobile robot path planning for its characteristics of simpleness, high efficiency, and smooth path. In this paper, to solve the problem of local minima in traditional artificial potential field method, A modified form of repulsion function is proposed. A detour force is added to the repulsion function, the problem of local minima can be solved effectively. In the end, with the help of Matlab software simulating, the result shows that this method is simple and effective.

Abstract: This paper proposes a new rolling algorithm for path plan of mobile robot based on automatically shunt the ant algorithm.The goal node is mapped to the node nearby the boundary in the eyeshot of the robot, and make out the best partial path, which the robot goes ahead for a step. The algorithm will iterate one time when the robot arrives at the goal node. The robot will reach the destination along the optimal path. Simulation experiments illustrate that the algorithm can be used to plan the optimal path for mobile robot even in the complex and unknown static environment.

Abstract: In this paper, an algebraic algorithm is developed with Min-algebra for the path planning problem of a simple weighted directed graph. According to the algebraic algorithm, the shortest path and its minimum steps will be concluded through the direct distance matrix A. Experimental results show that the algebraic algorithm is suitable for the path planning problem. The shortest path and its length can be gotten rapidly based on the proposed algorithm. Finally, the results are compared to those obtained by the conventional Dijkstra algorithm.

Abstract: In the research of robot path planning anti-collision method, with the traditional algorithm to plan robot path, the planning processis single, cumbersome and inefficient. To this end, a mobile robot path planning method based on potential field genetic fusion algorithm is proposed to establish the relationship model of different force in artificial potential field, and calculate attractive and repulsive forces applied on robotics in the artificial potential field, according to the attractive and repulsive forces to complete the anti-collision handling in route planning process. Experimental results show that the improved algorithm for anti-collision process in robot path planning, can effectively improve the computational efficiency for the anti-collision, expand its application field and enhance the technicality of anti-collision.

Abstract: Considering increasing importance of home service robot, the embedded control system based on TI msp430 and μC/OS-II is designed for window-cleaning robot. This paper includes three aspects, i.e., functions, hardware and software design. In the development of the system, the robot can be controlled by smart home system. PID controller is used to control DC motor stably. Meanwhile, a complete coverage path planning is proposed for efficiency.

Abstract: CAN bus was used as the data transferring channels in the two–level controllers, and the real-time,dexterity,expansibility and security for the Gluing control system based on CAN bus can be improved obviously.The system structure, principle and software design were introduced.The experiment shows that it is a reliable control system and it can meet the requirements of automatic gluing tasks.

Abstract: Aiming to solve the problem of mobile robot path planning, environmental models are established by using grid method at first, each grid is treated as a neuron, and then the whole space is changed into a topology-form one with all neutral net. Secondly, biological inspired neural networks (BINN) method towards neutral net is adopted to complete path planning of mobile robot. Furthermore, non-optimal solutions potentially produced in neutral net are modified in BINN. Simulation experiments show the feasibility and effectiveness of BINN method.

Abstract: With full rotation articulated ABB-IBR140-M2000 robot with six degrees of freedom used as welding robot, the exploring of efficient complete coverage of welding position flock is an important way of improving the performance of welding robot. Making use of improved genetic algorithm, in which the best father generation is saved and using ordered cross and reverse ordered mutation to constitute filial generation, and this method makes sure that the algorithms is convergent. The complete coverage of welding position optimization mathematic model whose objective is the minimum distance is established, making use of the improved genetic algorithm to solve the problem, an example is analyzed in detail, and the result shows that the algorithms is convergent and efficient.

Abstract: To address the problem of planning complete coverage paths for mowing robots that have the greatest coverage rates and the lowest repetitive rates, we proposed an improved back propagation neural network algorithm based on priority traversal thoughts for local path planning. The algorithm based on plowing global path planning. We adopted grid method to model the environment and used Matlab2010a to simulate for the algorithm. Simulation results show that the proposed algorithm can make the mowing robot walk out of dead zone, the dead zone was composed of obstacle grid or the grid that had been cut around this area, and achieve the complete coverage path planning.