A dynamic path planning approach for multi-robot sensor-based coverage considering energy constraints

Abstract

In this study, a novel dynamic path planning approach is proposed for multi-robot sensor-based coverage considering energy capacities of the mobile robots. The environment is assumed to be narrow and partially unknown. A Generalized Voronoi diagram-based network is used for the sensor-based coverage planning due to narrow nature of the environment. On the other hand, partially unknown nature is handled with proposed dynamic re-planning approach. Initially, the robots are assumed to be at the same depot with equal initial energy capacities. In this case, an initial complete coverage route is constructed considering robot energy capacities using classical capacitated arc routing problem (CARP) approach with some minor modifications related to coverage problem. But, due to partially unknown nature, the robots may face with blockage on routes, and a fast re-planning is required which considers remaining energy capacities and current positions of the robots. So, new plan is obtained by a modifying Ulusoy's algorithm that was developed for classical CARP. The developed algorithm is coded in C++ and implemented on P3-DX mobile robots in MobileSim simulation environment.

A unified framework for operational range estimation of mobile robots operating on a single discharge to avoid complete immobilization

“…In (Sadrpour et al, 2013;Broderick et al, 2014), researchers study the necessary energy and remaining battery life based on real-time performance data. Energy consumption minimization techniques have been focusing on trajectory and path planning (Liu and Sun, 2014;Kim and Kim, 2014;Yazici et al, 2009;Mei et al, 2004) and high level scheduling (Vergnano et al, 2010).…”

Estimating Achievable Range of Ground Robots Operating on Single Battery Discharge for Operational Efficacy Amelioration

“…Majority of these researches focus on reducing the energy consumption. Energy efficiency optimization has been applied to robot design [12], [15], locomotion principle [14], trajectory and path planning [11], [13], [16], [17], and high level scheduling [10]. However, quantifying and optimizing the energy consumption on a certain level does not provide an overview of the whole system consumption.…”

A Multi-Robot Control Architecture for Fault-Tolerant Sensor-Based Coverage

“…The planning phase constructs partial path plans which will be allocated to the robots. The partial plans are generated by using the RPP and the CARP-based solution approaches (Yazici et al, 2009). The environment is modeled by a Generalized Voronoi Diagram (GVD) based network G= (V,E).…”