Task Allocation and Route Planning for Robotic Service Networks in Indoor Building Environments

Abstract

Robots have become increasingly pervasive in day-to-day life, simplifying several monotonous and mundane tasks in indoor environments. With increasing applications being developed for domestic service robots, recent research emphasis has shifted to autonomous indoor robots. Route planning (determining optimal routes to visit multiple locations) and task allocation (optimally dividing the tasks assigned among a group of robots) are two of the critical aspects that have to be accomplished by single and multiple autonomous robotic systems. Previous studies have attempted to adapt existing algorithms used in outdoor logistics applications and modify them with context-specific assumptions, often leading to inefficient or suboptimal solutions. This paper addresses these issues and proposes a generalized framework to solve the route-planning and task-allocation problems for centrally located service robots charged with spatiotemporal tasks in complex built environments. A scenario analysis is conducted to compare the performance of existing algorithms with the developed approach for route planning in building-monitoring robots. The results demonstrate the feasibility of the proposed approach in a range of applications involving constraints on both the environment (e.g., path obstructions) and robot capabilities (e.g., maximum travel distance on single charge).