Abstract
The paper proposes the formulation of a single-task robot (ST), single-robot task (SR), time-extended assignment (TA), multi-robot task allocation (MRTA) problem with multiple, nonlinear criteria using discrete variables that drastically reduce the computation burden. Obtaining an allocation is addressed by a Branch and Bound (B&B) algorithm in low scale problems and by a genetic algorithm (GA) specifically developed for the proposed formulation in larger scale problems. The GA crossover and mutation strategies design ensure that the descendant allocations of each generation will maintain a certain level of feasibility, reducing greatly the range of possible descendants, and accelerating their convergence to a sub-optimal allocation. The proposed MRTA algorithms are simulated and analyzed in the context of a thermosolar power plant, for which the spatially distributed Direct Normal Irradiance (DNI) is estimated using a heterogeneous fleet composed of both aerial and ground unmanned vehicles. Three optimization criteria are simultaneously considered: distance traveled, time required to complete the task and energetic feasibility. Even though this paper uses a thermosolar power plant as a case study, the proposed algorithms can be applied to any MRTA problem that uses a multi-criteria and nonlinear cost function in an equivalent way. The performance and response of the proposed algorithms are compared for four different scenarios. The results show that the B&B algorithm can find the global optimal solution in a reasonable time for a case with four robots and six tasks. For larger problems, the genetic algorithm approaches the global optimal solution in much less computation time. Moreover, the trade-off between computation time and accuracy can be easily carried out by tuning the parameters of the genetic algorithm according to the available computational power.
Highlights
In recent decades, there have been great advances in the field of robotics with several works with humanoid robots [1], robotic arms [2] and in mobile robots or unmanned vehicles
The multi-robot task allocation (MRTA) problem has been formulated in the context of a thermosolar power plant where a Multi-robot systems (MRS) formed by various types of robots is in charge of collecting the Direct Normal Irradiance (DNI) data
We prioritize the use of a certain type of robot over the other or what is the same, to minimize the weighted distance traveled by the robots
Summary
There have been great advances in the field of robotics with several works with humanoid robots [1], robotic arms [2] and in mobile robots or unmanned vehicles. MRS can be used to tackle a set of tasks, which entails multiple advantages in comparison with the use of a single robot, i.e., complex tasks that are difficult to address by using a single robot might be solved by combining two or more robots, increasing global efficiency and decreasing task completion times
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.