For motion planning of concrete pump truck( CPT) with end-effector's hosepipe path, this paper sets up the mathematic model,including definition of its motion planning,description of its state in C space( configur...For motion planning of concrete pump truck( CPT) with end-effector's hosepipe path, this paper sets up the mathematic model,including definition of its motion planning,description of its state in C space( configuration space) and its path length. An advanced rapidly-exploring random trees( RRT) algorithm is proposed, in which each tracing point dispersed from the end hosepipe path can map multi-states of CPT so as to make variety of motion path of CPT. For increasing search efficiency and motion path quality,this algorithm generates any random states of CPT in certain probability to trend to the initial state or target state mapped with the end hosepipe path,and to have the least cost between this random state and its parent state. A typical case and two special cases are analyzed in which the end hosepipe paths are reciprocating linear trajectory and planar or spatial sine curves respectively. Their results verify the feasibility and validity of the proposed algorithm.展开更多
基金Nature Science Foundation of Liaoning Province,China(No.201102025)Dalian Science and Technology Plan Project,China(Nos.2012A17GX122,2013A16GX111)Fundamental Research Funds for the Central Universities,China(No.DUT14ZD221)
文摘For motion planning of concrete pump truck( CPT) with end-effector's hosepipe path, this paper sets up the mathematic model,including definition of its motion planning,description of its state in C space( configuration space) and its path length. An advanced rapidly-exploring random trees( RRT) algorithm is proposed, in which each tracing point dispersed from the end hosepipe path can map multi-states of CPT so as to make variety of motion path of CPT. For increasing search efficiency and motion path quality,this algorithm generates any random states of CPT in certain probability to trend to the initial state or target state mapped with the end hosepipe path,and to have the least cost between this random state and its parent state. A typical case and two special cases are analyzed in which the end hosepipe paths are reciprocating linear trajectory and planar or spatial sine curves respectively. Their results verify the feasibility and validity of the proposed algorithm.
