Path Planning Of Mobile Crane For Given Lifted Equipment Posture

As lifting environment becomes increasingly complex, the lifted equipments and cranes become more and more large-scale, lifting operation have higher requirements on safety, accuracy and efficiency. PPC is an important method to guarantee the safety and efficiency of lifting operation. What PPC study is how to obtain the action sequences under given conditions. We can eliminate the hazard such as overload and collision ahead of time when optimize the action sequences of crane through PPC. So the safety of lifting is guaranteed and the efficiency of project making is improved.A lot of scholars at home and abroad have studied the PPC problems, But most is conducted in the condition that initial lifting and on position posture of crane are known. However, in the actual lifting project, the initial and target posture of lifted equipment are given, in this case, the corresponding postures of crane are always undetermined and difficult to determine, then the operator always determine by experience. This thesis focuses on the PPMCGLEP problem to study.Firstly, this thesis analyses the kinematics of mobile crane and give the pseudo-analytic method of crane inverse kinematics to the special structure of crane. Thus we can obtain the corresponding posture of crane by the given posture of lifted equipments.Secondly, based on the depth study on robot path planning, this thesis suggests a general solution process of PPMCGLEP, give the modeling method of crane, lifted equipments and lifting environment in Path Planning, and construct the configuration space of PPC.Finally, this thesis studies two concrete issues of single PPMC(no moving action and considering moving action of crane). The location of crane is optimized to the first issue, proved by the practice case, the time of PPC is greatly reduced and the quality of path is more improved after the location optimization of crane. HeurPostureRRT algorithm is proposed for the situation that the initial position of lifted equipment is far away from the target position and the lifting environment is complicated, proved by the practice case, this algorithm greatly shorten the planning time and improve the path quality to the PPC problem whose lifting environment is complex.