Human–Robot Cooperation Using Multi-Agent-Systems
Journal of Intelligent and Robotic Systems
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
Cooperative multi-robot box-pushing
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 3 - Volume 3
Cost-balanced cooperation protocol in multi-agent robotic systems
ICPADS '96 Proceedings of the 1996 International Conference on Parallel and Distributed Systems
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Two-level of nondominated solutions approach to multiobjective particle swarm optimization
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A multi-agent architecture with cooperative fuzzy control for a mobile robot
Robotics and Autonomous Systems
A Multi-Objective Pareto-Optimal Solution to the Box-Pushing Problem by Mobile Robots
EMS '08 Proceedings of the 2008 Second UKSIM European Symposium on Computer Modeling and Simulation
Multiobjective programming using uniform design and genetic algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Handling multiple objectives with particle swarm optimization
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Multi-Robot box-pushing using non-dominated sorting bee colony optimization algorithm
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
Hi-index | 0.00 |
The paper proposes a novel formulation of the classical box-pushing problem by mobile robots as a multi-objective optimization problem, and presents Pareto optimal solution to the problem using Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed method adopts local planning scheme, and allows both turning and translation of the box in the robots' workspace in order to minimize the consumption of both energy and time. The planning scheme introduced here determines the magnitude of the forces applied by two mobile robots at specific location on the box in order to align and translate it along the time- and energy- optimal trajectory in each distinct step of motion of the box. The merit of the proposed work lies in autonomous selection of translation distance and other important parameters of the robot motion model using NSGA-II. The suggested scheme, to the best of the authors' knowledge, is a first successful realization of a communication-free, centralized cooperation between two robots used in box shifting problem satisfying both time and energy minimization objectives simultaneously, presuming no additional user-defined constraint on the selection of linear distance traversal.