Automatic robot path planning with constraints
In a complex and flexible manufacturing environment tasks maybe dynamically reconfigured. In this situation a robot needs to plan paths automatically to avoid obstacles and rendezvous with changing target points. A novel path planning system is presented which takes into account both kinematic and dynamic constraints. The main part of the system comprises a robot "Path Planner" and "Path Adapter", both using a dynamic "World Model" updated by a vision system. The Path Planner contains a geometric model of the static environment and the robot. Given a task, the Path Planner calculates an efficient collision free path. This is passed to the control computer where a trajectory is generated. Pre-determination of optimum paths using established techniques frequently involve unacceptably high time penalties. To overcome this problem the automatic path refinement techniques employed avoid the necessity for optimality before beginning a movement. Repeated improvements to the sub optimal paths initially generated by the Path Planner are made until the robot is ready to begin the new path. Algorithms are presented which give a rapid solution for simplified obstacle models. The algorithms are robust and are especially suitable for repetitive robot tasks. With the Path Planner, the robot structure is modelled as connected cylinders and spheres and the range of robot motion is quantised. The robot path, calculated initially only takes account of geometric, kinematic and obstacle constraints. Although this path is sub optimal, the calculation time is short. The path avoids obstacle and seeks the "shortest" path in terms of total actuator movement. Several of the new path planning methods presented employ a local method, taking a "best guess" at a path through a 2-D space for two joints and then calculating a path for the third joint such that obstacles are avoided. A different approach is global and depends on searching a 3-D graph of quantised joint space. The Path Planner works in real time. If there is enough time available a "Path Adapter" modifies the planned path in an effort to improve the path subject to selected criteria. The Path Adapter considers dynamic constraints. The first robot path improvement method depends on detecting the joint motor currents in order to minimise changes in joint direction, the other is based on a set of adaptive rules based on simplified dynamic software models of the robot stored within the planning computer. The adapted path is passed to the control computer. The static model of the robot work-cell is held in computer memory as several solid polyhedral. With the aid of a vision system, this model is updated as new obstacles enter or leave the work-place. Overlapping spheres and 2-D slices in joint space are used to model obstacles. In this form the vision system can be updated quickly and the obstacle data can de accessed efficiently by the path planning and path improvement algorithms.