通过混合现实技术弥合无人机群开发中的现实差距

IF 3.7 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Autonomous Robots Pub Date : 2024-09-30 DOI:10.1007/s10514-024-10169-1
Micha Sende, Christian Raffelsberger, Christian Bettstetter
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引用次数: 0

摘要

蜂群算法有望解决大型多机器人系统中的某些问题。然而,对大型机器人群的评估具有挑战性,因为仅靠模拟往往缺乏真实系统的某些特性,而真实世界的实验成本高昂且复杂。我们介绍了一种混合现实(MR)系统,该系统通过 5G 网络连接模拟机器人和物理机器人,促进了基于通信的机器人群算法评估的混合现实实验。通过与无人驾驶飞行器的广泛实验,证明了该系统的有效性。测量结果表明,5G 可以很好地满足蜂群协调的通信要求,但模拟服务器的计算能力可能会成为瓶颈。不过,即使模拟速度减慢,通信和协调也能实时进行。总之,支持 5G 的磁共振实验是弥合机器人群开发和评估现实差距的可行工具。
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Bridging the reality gap in drone swarm development through mixed reality

Swarm algorithms promise to solve certain problems in large multi-robot systems. The evaluation of large swarms is however challenging as simulations alone often lack some properties of real systems whereas real-world experiments are costly and complex. We present a mixed reality (MR) system that connects simulated and physical robots though a 5G network, facilitating MR experiments to evaluate communication-based swarm algorithms. The effectiveness of the system is demonstrated through extensive experiments with unmanned aerial vehicles. Measurements show that the communication requirements of swarm coordination are well met by 5G but the computing power of the simulation server can be a bottleneck. However, even when the simulation slows down, communication and coordination take place in real time. In conclusion, 5G-enabled MR experiments are a feasible tool for bridging the reality gap in the development and evaluation of robot swarms.

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来源期刊
Autonomous Robots
Autonomous Robots 工程技术-机器人学
CiteScore
7.90
自引率
5.70%
发文量
46
审稿时长
3 months
期刊介绍: Autonomous Robots reports on the theory and applications of robotic systems capable of some degree of self-sufficiency. It features papers that include performance data on actual robots in the real world. Coverage includes: control of autonomous robots · real-time vision · autonomous wheeled and tracked vehicles · legged vehicles · computational architectures for autonomous systems · distributed architectures for learning, control and adaptation · studies of autonomous robot systems · sensor fusion · theory of autonomous systems · terrain mapping and recognition · self-calibration and self-repair for robots · self-reproducing intelligent structures · genetic algorithms as models for robot development. The focus is on the ability to move and be self-sufficient, not on whether the system is an imitation of biology. Of course, biological models for robotic systems are of major interest to the journal since living systems are prototypes for autonomous behavior.
期刊最新文献
Optimal policies for autonomous navigation in strong currents using fast marching trees A concurrent learning approach to monocular vision range regulation of leader/follower systems Correction: Planning under uncertainty for safe robot exploration using gaussian process prediction Dynamic event-triggered integrated task and motion planning for process-aware source seeking Continuous planning for inertial-aided systems
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