Cooperative transport by multiple mobile robots in unknown static environments associated with real-time task assignment

Abstract

This paper deals with a task-assignment architecture for cooperative transport by multiple mobile robots in an unknown static environment. The architecture should satisfy three features: deal with a variety of tasks in time and space, deal with a large number of tasks compared with the number of robots, and decide behavior in real time. The authors propose the following approach: We consider the unit of task (task instance) as the job that should be done in a short time by one robot. Based on environmental information, task instances are dynamically generated using task templates. The priority of task instances is evaluated dynamically based on the number of robots and the configuration in the workspace. In addition, we avoid generating too many task instances by suppressing object motion. The main part of the architecture consists of two real-time planners: a priority-based task-assignment planner solved by using a linear programming method, and motion planners based on short-time estimation. The effectiveness of the proposed architecture is verified by a cooperative transport simulation in an unknown environment.

Solving the task variant allocation problem in distributed robotics

“…The work presented in the earlier sections of this paper is classified as XD-SR-MT-IA. Thus, by comparison, the search space of our work is several orders of magnitude larger than the maximum search space presented in related work in this category (Lagoudakis et al 2004;Lozenguez et al 2013;Luo et al 2015;Miyata et al 2002;Sujit et al 2006;Zhao et al 2016;Nunes et al 2012;Mosteo and Montano 2007;Tolmidis and Petrou 2013;Okamoto et al 2011). …”

“…all tasks and processors may be different. Some past work does assume heterogeneous tasks and multiple instances of every task (Miyata et al 2002), but does not consider different variants of the same task, which is the principal addition to the problem here.…”

Modelling computational requirements of mobile robotic systems using zones and processing windows

“…Examples of applying the real-time scheduling to robotics can be found in [7,9,22,3,17,18,23,2,16,10,13,14]. Of these, rate monotonic (RM) [15] scheduling was used in [9,22,3,17]; earliest deadline first (EDF) [15] scheduling was used in [17,23]; and feedback based scheduling techniques in [22,10,14].…”

“…Of these, rate monotonic (RM) [15] scheduling was used in [9,22,3,17]; earliest deadline first (EDF) [15] scheduling was used in [17,23]; and feedback based scheduling techniques in [22,10,14]. The work in [16,13] used real-time scheduling theory to assign tasks to robots in a team of mobile robots. While these papers applied real-time scheduling theory to a robotic application, none of them considered the execution requirements of the platform's sensing and planning as a factor in the platform's velocity calculations.…”

“…Miyata et al [16] developed a task assignment system for a team of robots handling flexible materials. Their task assignment algorithm used task templates to divide the work done by robots into tasks and assigned the tasks to robots based on the number of free robots and task priorities.…”