Assembling a Swarm Navigation System: Communication, Localization, Sensing and Control

Zhang, Siwei; Pöhlmann, Robert; Staudinger, Emanuel; Dammann, Armin

doi:10.1109/ccnc49032.2021.9369547

Cited by 14 publications

(19 citation statements)

References 31 publications

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“…The physical layer signaling is based on our in-house developed DLR Swarm Communication and Navigation system [52], [54] Software Radio Peripheral (USRP) B200mini devices are used for the nodes with singleport antennas. On Dias, the USRP N310 from Ettus Research with four transceiver channels is installed.…”

Section: A Measurement Setupmentioning

confidence: 99%

Simultaneous Localization and Calibration for Cooperative Radio Navigation

Pöhlmann

Zhang

Staudinger

et al. 2022

IEEE Trans. Wireless Commun.

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Cooperative radio localization and navigation systems can be used in scenarios where the reception of global navigation satellite system (GNSS) signals is not possible or impaired. While the benefit of cooperation has been highlighted by many papers, calibration is not widely considered, but equally important in practice. Utilizing the signal propagation time requires group delay or ranging bias calibration and estimating the direction-of-arrival (DoA) requires antenna response calibration. Often, calibration parameters are determined only once before operation. However, the calibration parameters are influenced by e.g. changing temperatures of radio frequency (RF) components or changing surroundings of antennas. To cope with that, we derive a cooperative simultaneous localization and calibration (SLAC) algorithm based on Bayesian filtering, which estimates antenna responses and ranging biases simultaneously with positions and orientations. By simulations, we show that the calibration parameters can be estimated during operation without additional sensors. We further proof practical applicability of SLAC by evaluating measurement data from robotic rovers. With SLAC, both ranging and DoA estimation performance is improved, resulting in better position and orientation estimation accuracy. SLAC is thus able to provide reliable calibration and to mitigate model mismatch. Finally, we discuss open research questions and possible extensions of SLAC.

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Section: A Measurement Setupmentioning

confidence: 99%

Simultaneous Localization and Calibration for Cooperative Radio Navigation

Pöhlmann

Zhang

Staudinger

et al. 2022

IEEE Trans. Wireless Commun.

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“…In these scenarios, static boxes or rovers are deployed at preferable positions as relays to guarantee reliable communication. The third scenario demonstrates the autonomous deployment of a LOFAR, which is illustrated in As a preparation to this space analog mission, we have conducted a LOFAR experiment with our developed swarm navigation platform [7] at the German Aerospace Center (DLR) in March 2021. The experimental setup with four LOFAR boxes and two low frequency transmitters is shown in Figure 6.…”

Section: B Experimentsmentioning

confidence: 99%

“…In this paper, we have a joint look at the communication, localization, sensing and control aspects in an exploration mission, which is essential for design such an autonomous robotic network [7], [8]. Depending on the overall mission objectives, the trade-off between communication and localization determines the favorable swarm formations.…”

Section: Introductionmentioning

confidence: 99%

“…Low frequency radio signals emitted either from space or by an artificial transmitter are detected by this array. As we discussed in Section II, in this scenario the most demanding requirement is localization.As a preparation to this space analog mission, we have conducted a LOFAR experiment with our developed swarm navigation platform[7] at the German Aerospace Center (DLR) in March 2021. The experimental setup with four LOFAR boxes and two low frequency transmitters is shown in Figure6.…”

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confidence: 99%

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Cooperative Communication, Localization, Sensing and Control for Autonomous Robotic Networks

Zhang

Staudinger

Pöhlmann

et al. 2021

2021 IEEE International Conference on Autonomous Systems (ICAS)

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Networks composed of a myriad of autonomous robots have attracted increasing attention in recent years due to their enormous capability expansion from single robot systems. In these networks, robots benefit from the collaboration with each other to enhance their situation awareness for autonomous operation. For example, in an extraterrestrial exploration mission, a robotic swarm can collaboratively utilize the inter-robot communication system to propagate information, synchronize itself, and navigate to achieve mission objectives like joint environmental sensing. In addition, each robot can decide and control its own trajectory, so that the aforementioned tasks are accomplished in a globally efficient manner. In this paper, we propose multi-agent control strategies for autonomous robotic networks, which adapt the mission demands on cooperative communication, localization and sensing. We also discuss three space exploration examples with different mission demands, which lead to distinct network formations. These three missions will be conceptually demonstrated in a space analog mission on the volcano Mount Etna in June 2022.

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“…As typical automatic systems, the operation of UAVs or UAV swarms requires appropriate design and coordination of sensing, communication and control functionalities [16]. In existing systems, these three functionalities were commonly designed and implemented separately, which was previously thought to be conducive to ensuring compatibility among different functionalities [17].…”

Section: A Motivationmentioning

confidence: 99%

QoS-Oriented Sensing-Communication-Control Co-Design for UAV-Enabled Positioning

Wang¹,

Liu²,

Liu³

et al. 2021

Preprint

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Unmanned aerial vehicle (UAV)-enabled positioning that uses UAVs as aerial anchor nodes is a promising solution for providing positioning services in harsh environments. In previous research, the state sensing and control of UAVs were either ignored or simply set to be performed continuously, resulting in system instability or waste of wireless resources. Therefore, in this article, we propose a quality-of-service (QoS)-oriented UAV-enabled positioning system based on the concept of sensingcommunication-control (SCC) co-design. We first establish the mathematical models of UAV state sensing and control. Then, the influence of sensing scheduling and transmission failure on UAV stability, as well as the performance of positioning services in the presence of UAV control error, are analyzed.Based on these models and analysis results, we further study the problem of minimizing the amount of data transmitted by optimizing the sensing scheduling and blocklength allocation under the condition of satisfying each user's demand. Finally, an efficient scheme is developed to solve this mixed-integer nonlinear problem. Numerical results show that the proposed system could work efficiently and meet users' requirements. In addition, compared with two benchmark schemes, our scheme reduces the failure rate or resource consumption of positioning services by more than 76.2% or 82.7%.

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Assembling a Swarm Navigation System: Communication, Localization, Sensing and Control

Cited by 14 publications

References 31 publications

Simultaneous Localization and Calibration for Cooperative Radio Navigation

Simultaneous Localization and Calibration for Cooperative Radio Navigation

Cooperative Communication, Localization, Sensing and Control for Autonomous Robotic Networks

QoS-Oriented Sensing-Communication-Control Co-Design for UAV-Enabled Positioning

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