Multi-objective heuristics applied to robot task planning for inspection plants

Abstract

Robotics are generally subject to stringent operational conditions that impose a high degree of criticality on the allocation of resources and the schedule of operations in mission planning. In this regard the so-called cost of a mission must be considered as an additional criterion when designing optimal task schedules within the mission at hand. Such a cost can be conceived as the impact of the mission on the robotic resources themselves, which range from the consumption of battery to other negative effects such as mechanic erosion. This manuscript focuses on this issue by presenting experimental results obtained over realistic scenarios of two heuristic solvers (MOHS and NSGA-II) aimed at efficiently scheduling tasks in robotic swarms that collaborate together to accomplish a mission. The heuristic techniques resort to a Random-Keys encoding strategy to represent the allocation of robots to tasks whereas the relative execution order of such tasks within the schedule of certain robots is computed based on the Traveling Salesman Problem (TSP). Experimental results in three different deployment scenarios reveal the goodness of the proposed technique based on the Multi-objective Harmony Search algorithm (MOHS) in terms of Hypervolume (HV) and Coverage Rate (CR) performance indicators.

An Efficient Scheduling Algorithm for Multi-Robot Task Allocation in Assembling Aircraft Structures

“…The partitioned work is scheduled by sequencing all the tasks in every partition in the same axial direction and offset the start locations of all the robots on one side (top or bottom) of the work part as shown in Figure 1 1 . We denote the i-th offset and non-offset robots as top r i t and bottom r i b robots (as in Figure 1), respectively, but either the top or bottom robot can be offset in practice.…”

“…The failure instances were generated for each robot by randomly drawing a first occurrence time, recurrence time, and repair time from normal distributions. The means and standard deviations of the distributions were determined using a nominal value of how many holes a 1 4 inch drill bit would last in aluminum and an average drill bit replacement time. These were taken to be 300 holes and 8 minutes, respectively.…”

“…Aircraft structure assembly is a large-scale manufacturing process with many repeated subprocesses such as drilling, fastening, trimming, and painting that naturally lend themselves to automation. Using multiple robots to work cooperatively offers a means of increasing the production speed, and hence, multi-robot systems (MRSs) have been widely studied in manufacturing applications [1]- [3]. Here, we consider the efficient scheduling of such an MRS (comprising multiple stationary robotic manipulators with limited but overlapping reach) during the assembly of large aircraft structures such as the wing and fuselage.…”