Rapid path planner plays an important role in autonomous ground vehicle (AGV) operation. Depending on the non-holonomic kinematics constraints of AGV, its path planning problem is discussed. Since rapidly-exploring ra...Rapid path planner plays an important role in autonomous ground vehicle (AGV) operation. Depending on the non-holonomic kinematics constraints of AGV, its path planning problem is discussed. Since rapidly-exploring random tree (RRT) can directly take non-holonomic constraints into consideration, it is selected to solve this problem. By applying extra constraints on the movement, the generation of new configuration in RRT algorithm is simplified and accelerated. With section collision detection method applied, collision detection within the planer becomes more accurate and effcient. Then a new path planner is developed. This method complies with the non-holonomic constraints, avoids obstacles effectively and can be rapidly carried out while the vehicle is running. Simulation shows that this path planner can complete path planning in less than 0.5 s for a 170 m×170 m area with moderate obstacle complexity.展开更多
基金Project (HEUCFR1128) supported by the Fundamental Research Funds for the Central Universities,ChinaProject (2010AA4BE031)supported by the Key Project of Science and Technology of Harbin City,China+1 种基金Projects (20100471015,20100471046) supported by the China Postdoctoral Science FoundationProject (LBH-Z09217) supported by the Heilongjiang Postdoctorial Fund,China
文摘Rapid path planner plays an important role in autonomous ground vehicle (AGV) operation. Depending on the non-holonomic kinematics constraints of AGV, its path planning problem is discussed. Since rapidly-exploring random tree (RRT) can directly take non-holonomic constraints into consideration, it is selected to solve this problem. By applying extra constraints on the movement, the generation of new configuration in RRT algorithm is simplified and accelerated. With section collision detection method applied, collision detection within the planer becomes more accurate and effcient. Then a new path planner is developed. This method complies with the non-holonomic constraints, avoids obstacles effectively and can be rapidly carried out while the vehicle is running. Simulation shows that this path planner can complete path planning in less than 0.5 s for a 170 m×170 m area with moderate obstacle complexity.
