Time Bound Robot Mission Planning for Priority Machine Using Linear Temporal Logic for Multi Goals

In this paper, we implement a Linear Temporal Logic-based motion planning algorithm for a prioritized mission scenario. The classic robot motion planning solves the problem of moving a robot from a source to a goal configuration while avoiding obstacles. This problem of motion planning gets complicated when the robot is asked to solve a complex goal specification incorporating boolean and temporal constraints between the atomic goals. This problem is referred to as the mission planning. The paper assumes that the mission to be solved is a collection of smaller tasks, wherein each task constituting the mission must be finished within a given amount of time. We assign the priorities for the tasks such that, the higher priority tasks should be completed beforehand. The planner solves the missions in multiple groups, instead of the classic approach of solving all the tasks at once. The group is dynamic and is a function of how many tasks can be incorporated such that no time deadline is lost. The grouping based prioritized and time-based planning saves a significant amount of time as compared to the inclusion of time information in the verification engine that complicates the search logic. NuSMV tool is used to verify the logic. Comparisons are made by solving all tasks at once and solving the tasks one-by-one. Experimental results reveal that the proposed solver is able to meet the deadlines of nearly all tasks while taking a small computation time.