首页 /研究 /Cooperative Search by Combining Simulated and Real Robots in a Swarm under the View of Multibody System Dynamics
SWARM

Cooperative Search by Combining Simulated and Real Robots in a Swarm under the View of Multibody System Dynamics

Qirong Tang, Peter Eberhard

发表年份
2013
引用次数
5

摘要

This paper presents a new approach for cooperative search of a robot swarm. After modeling the robot, the mechanical Particle Swarm Optimization method is conducted based on physical robot properties. Benefiting from the effective localization and navigation by sensor data fusion, a mixed robot swarm which contains both simulated and real robots is then successfully used for searching a target cooperatively. With the promising results from experiments based on different scenarios, the feasibility, the interaction of real and simulated robots, the fault tolerance, and also the scalability of the proposed method are investigated.

关键词

RobotSwarm roboticsSwarm behaviourParticle swarm optimizationScalabilityComputer scienceArtificial intelligenceMachine learning

相关论文

查看 SWARM 分类全部论文