One of the tools required for autonomous robots is automated motion generation for the interception of moving objects. The Active Prediction Planning and Execution (APPE) strategy provides one approach for solving this problem. In this strategy the motion of an object through a robot's work-space is predicted. Robot motion to intercept the object is then planned and executed. These three stages are repeated to ensure successful task completion. This research addresses the development of APPE planning strategies for the robotic interception of moving objects.

The object-interception problem requires a time-dependent trajectory-planning solution. The objective is to bring the robot end-effector to a pre-grasping target-location with respect to the object using a gross motion trajectory-planning strategy, so that a finemotion tracking strategy can be used to grasp the object.

The APPE approach allows the minimization of the time-to-interception. To achieve this minimization, two problems must be solved:​ (i) selection of an optimal rendezvous-point;​ and, (ii) planning of a time-optimal robot-trajectory to this rendezvous-point. These issues are addressed in tandem in order to achieve global time-optimal results.

The optimal rendezvous-point-planning problem requires searching the predicted target-trajcctory for the earliest rendezvous-point such that the robot end-effector and the target can arrive simultaneously at the same location. The optimal point-to-point robot-trajectory-planning problem is further divided into two stages, to reduce complexity in exchange for some loss in motion-time optimality. The two stages are:​ (i) selection of a (near-optimal) joint-space path for the robot motion;​ and, (ii) generation of global-optimal joint trajectories along this path.

One of the implications of a time dependent planning strategy is that uncertainties must be expected and tolerated. Herein, uncertainties are considered in two stages:​ as a convergence criterion in the initial planning stage;​ and, as a triggering mechanism for planning a new rendezvous-point in the re-planning stage.

The planning strategies were verified within a generic APPE system via simulations to solve a number of object-interception problems addressed in the literature. In one particular case, the planning strategies were implemented within a specific APPE system to provide a direct comparison with the previous approach reported in the cited work.