군집 로봇의 임무 검증 지원을 위한디지털 트윈 기반 통신 최적화 기법
Digital Twin-Based Communication Optimization Method for Mission Validation of Swarm Robot
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초록
로봇은 군사 분야로까지 활용 범위를 넓히며 다가올 미래전에서 감시경계, 적군 탐지 등 중요한 임무를 맡게 될 것으로 전망된다. 군집 로봇은다수라는 장점으로 단일 로봇이 수행하기 어렵거나 오랜 시간이 소요된 임무를 보다 효율적으로 수행할 수 있다. 상호 간 인지 및 협업이 필수인군집 로봇은 방대한 데이터를 주고 받으며, 이로 인해 SW의 검증이 점점 더 어려워지고 있다. 임무 검증의 신뢰성을 높이기 위해 사용하는Hardware-in-the-loop simulation은 복잡한 군집 로봇의 SW 검증을 가능하게 하나, HILS 장치와 시뮬레이터 간 주고 받는 검증 데이터의 양이검증 대상 시스템 수에 따라 기하급수적으로 증가하여 통신 과부하가 발생할 수 있다. 본 논문에서는 군집 로봇의 임무 검증에서 발생하는 통신과부하 문제를 해소하기 위해 디지털 트윈 기반의 통신 최적화 기법을 제안한다. 제안하는 Digital Twin based Multi HILS Framework 하에서Network DT은 Network Controller 알고리즘을 통해 임무 시나리오에 따라 각 로봇에게 네트워크 자원을 효율적으로 할당할 수 있으며, 군집에참여하는 개별 로봇들이 요구하는 Sensor Generation Rate를 모두 만족시킬 수 있음을 확인하였다. 또한 데이터 전송에 대한 실험 결과 패킷손실 비율을 기존 15.7%에서 약 0.2%로 감소시킬 수 있었다.
Abstract
Robots are expected to expand their scope of application to the military field and take on important missions such as surveillanceand enemy detection in the coming future warfare. Swarm robots can perform tasks that are difficult or time-consuming for a singlerobot to be performed more efficiently due to the advantage of having multiple robots. Swarm robots require mutual recognition andcollaboration. So they send and receive vast amounts of data, making it increasingly difficult to verify SW. Hardware-in-the-loop simulationused to increase the reliability of mission verification enables SW verification of complex swarm robots, but the amount of verificationdata exchanged between the HILS device and the simulator increases exponentially according to the number of systems to be verified. So communication overload may occur. In this paper, we propose a digital twin-based communication optimization technique to solvethe communication overload problem that occurs in mission verification of swarm robots. Under the proposed Digital Twin based MultiHILS Framework, Network DT can efficiently allocate network resources to each robot according to the mission scenario through theNetwork Controller algorithm, and can satisfy all sensor generation rates required by individual robots participating in the group. Inaddition, as a result of an experiment on packet loss rate, it was possible to reduce the packet loss rate from 15.7% to 0.2%.
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