Multi-robot sensor-based coverage path planning using capacitated arc routing approach

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

“…The first case can be solved using with MUA proposed in [7]. This case usually can be faced during the initial plan where robots are fully charged and in the same depot.…”

“…Hence, different heuristic algorithms are developed in the literature such as Simple constructive methods (Construct-Strike, ModifiedConstruct-Strike, Path-Scanning, Augment-Merge algorithm, Parallel Insert Algorithm, Augment-Insert Algorithm), two-phase constructive methods (UlusoyPartitioning algorithm [12], Cut Algorithm and Cycle Assignment algorithm [13]), and metaheuristics (Tabu search-based algorithms [14] and genetic algorithms [15]). In [7], a minor modification was done on Ulusoy's partitioning algorithm to handle multi-robot sensor-based coverage path planning problem for the same depot point and equal energy capacity. Assume that ij e denotes energy consumption during the travel through edge due to motors, micro controller units, etc., and ij q denotes required energy for sensor coverage and traveling on the edge ) , (…”

“…Because of this difference, CARP solution techniques can not be used directly for the sensor-based coverage problem with multiple robots. In [7], this difference between the classical CARP problem and the coverage problem explained and solved by some minor modification to Ulusoy's algorithm that is used for classical CARP. The method proposed in [7] was used to construct initial coverage routes for a robot team under the assumption that the robots start from the same depot point and they have equal energy capacities (all fully charged).…”

“…In [7], this difference between the classical CARP problem and the coverage problem explained and solved by some minor modification to Ulusoy's algorithm that is used for classical CARP. The method proposed in [7] was used to construct initial coverage routes for a robot team under the assumption that the robots start from the same depot point and they have equal energy capacities (all fully charged). But, if robots face with a blocking obstacle due to partially unknown nature of the environment, a fast re-planning is required.…”

Coefficient of agility and sampling frequency issues in Mobile Agents Collision Detection with Dynamic Obstacles in 3D Space

“…Series of research were conducted related to control algorithm and hardware configuration [17] [18], as well as group of robots [19] and robots formations [20]. Relevant to this research is robots collaboration [21] and multi-robots networks [22] [23] [24]. There is proposed generic algorithm [25] and reference generation and control schemes [26].…”