یک الگوریتم برنامه ریزی مسیر برای روبات های صنعتی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|18216||2002||10 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Computers & Industrial Engineering, Volume 42, Issues 2–4, 11 April 2002, Pages 299–308
Instead of using the tedious process of robot teaching, an off-line path planning algorithm has been developed for industrial robots to improve their accuracy and efficiency. Collision avoidance is the primary concept to achieve such goal. By use of the distance maps, the inspection of obstacle collision is completed and transformed to the configuration space in terms of the robot joint angles. On this configuration map, the relation between the obstacles and the robot arms is obvious. By checking the interference conditions, the collision points are indicated with marks and collected into the database. The path planning is obtained based on the assigned marked number of the passable region via wave expansion method. Depth-first search method is another approach to obtain minimum sequences to pass through. The proposed algorithm is experimented on a 6-DOF industrial robot. From the simulation results, not only the algorithm can achieve the goal of collision avoidance, but also save the manipulation steps.
Many researches have been investigated on the path planning for various objectives such as minimum time, minimum energy, and obstacle avoidance. Regarding obstacle avoidance, distance maps is to divide the space by grids with equal distance (Latombe, 1991 and Jarvis, 1993). On the intersection of grids are the nodes, which is marked with numbers for collision inspection. Configuration space method proposed by Lozano-Perez, 1983 and Lozano-Perez, 1987 is able to represent the robot manipulation geometry via the joint space. For an n degree-of-freedom robot, there is n dimensional vector to define the manipulation. The free space approach is to search the obstacles with encircled boundaries, which form various shapes of cones. Then, the centerlines of the generalized cones are the path planned to move along ( Brooks, 1983a and Brooks, 1983b). Visibility graph algorithm connects each apex of the obstacle so as to obtain the passable area, in which the likely desired paths are generated ( Oomen, Iyengar, Rao, & Kashyap, 1987). A method is developed by means of the hierarchical tree structure, which utilizes, in general, the quadtree to segment the workspace into numerous areas represented by nodes ( Samet, 1990). The nodes are categorized into the obstacle nodes and free nodes, which denote the obstructive area and passable area, respectively. The free nodes are connected to form a tree structure that provides the method of path planning.
نتیجه گیری انگلیسی
The proposed algorithm attempts to search a path not only can avoid the obstacles but save the manipulation steps. Fast inspection approach saves the computation time in determining the passable areas. In the configuration space, the wave-expansion and depth-first search algorithms are applied to define the obstructive area and the passable area so that the likely path is obtained. The depth-first search method needs fewer manipulation steps than the wave expansion method does. The latter one uses the neighbor nodes to search a path. It needs less computation time, however, the manipulation steps may be more. On the other hand, the former one with the search tree approach intensively inspects all passable nodes, therefore, it guarantees to obtain a path with minimum manipulation steps, but it costs more computation time. The developed algorithm is expected to be able to deal with miscellaneous obstacles in the practical working environment. Further experiment needs to be carried out to evaluate the efficiency (Lei, 1999). The chosen unit distance between the grids of each link, which may affect the path planning, is being investigated. The reduction of the manipulation steps may save the manipulation time, which is an important concern for industrial automation. It needs comprehensive study to verify the correlation.