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Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing.

Park C, Cho N, Lee K, Kim Y - Sensors (Basel) (2015)

Bottom Line: Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs.Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed.The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechanical & Aerospace Engineering, Seoul National University, Daehak-dong, Gwanak-gu, Seoul 151-744, Korea. bakgk@snu.ac.kr.

ABSTRACT
To monitor large areas or simultaneously measure multiple points, multiple unmanned aerial vehicles (UAVs) must be flown in formation. To perform such flights, sensor information generated by each UAV should be shared via communications. Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs. In this study, an onboard sensor information sharing system and formation flight algorithms for multiple UAVs are proposed. The communication delays of radiofrequency (RF) telemetry are analyzed to enable the implementation of the onboard sensor information sharing system. Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed. The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform. A numerical simulation is performed to demonstrate the performance of the formation flight guidance and control system for multiple UAVs. Finally, a flight test is conducted to verify the proposed algorithm for the multi-UAV system.

No MeSH data available.


(a) Embedded FCCs and GCS; (b) sequential cyclic communication.
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sensors-15-17397-f007: (a) Embedded FCCs and GCS; (b) sequential cyclic communication.

Mentions: The considered ZigBee modem, Xbee-Pro DigiMesh900, has a baud rate of 230,400 bps and an air rate of 156,000 bps. In this case, nearly 24 ms passes between the first transmission to the second transmission for the n = 124-byte case. The total communication delay can be measured using a signal analyzer; as shown in Figure 6, 10 Hz of onboard sensor information sharing is possible because one cycle of four UAVs takes 24 ms × 4 = 96 ms. Accurate 10 Hz cyclic communication can be achieved if the FCC has less than 4 ms of additional processing delay. Because the typical minimum time interval of Microsoft Windows OS is in the range of 10 ms–20 ms, the Windows OS is not suitable for handling the cyclic communication. In this study, a real-time embedded FCC is used because it can control the communication timing with a 1 ms resolution. The developed embedded FCC and cyclic communication sequence is shown in Figure 7.


Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing.

Park C, Cho N, Lee K, Kim Y - Sensors (Basel) (2015)

(a) Embedded FCCs and GCS; (b) sequential cyclic communication.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541940&req=5

sensors-15-17397-f007: (a) Embedded FCCs and GCS; (b) sequential cyclic communication.
Mentions: The considered ZigBee modem, Xbee-Pro DigiMesh900, has a baud rate of 230,400 bps and an air rate of 156,000 bps. In this case, nearly 24 ms passes between the first transmission to the second transmission for the n = 124-byte case. The total communication delay can be measured using a signal analyzer; as shown in Figure 6, 10 Hz of onboard sensor information sharing is possible because one cycle of four UAVs takes 24 ms × 4 = 96 ms. Accurate 10 Hz cyclic communication can be achieved if the FCC has less than 4 ms of additional processing delay. Because the typical minimum time interval of Microsoft Windows OS is in the range of 10 ms–20 ms, the Windows OS is not suitable for handling the cyclic communication. In this study, a real-time embedded FCC is used because it can control the communication timing with a 1 ms resolution. The developed embedded FCC and cyclic communication sequence is shown in Figure 7.

Bottom Line: Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs.Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed.The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechanical & Aerospace Engineering, Seoul National University, Daehak-dong, Gwanak-gu, Seoul 151-744, Korea. bakgk@snu.ac.kr.

ABSTRACT
To monitor large areas or simultaneously measure multiple points, multiple unmanned aerial vehicles (UAVs) must be flown in formation. To perform such flights, sensor information generated by each UAV should be shared via communications. Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs. In this study, an onboard sensor information sharing system and formation flight algorithms for multiple UAVs are proposed. The communication delays of radiofrequency (RF) telemetry are analyzed to enable the implementation of the onboard sensor information sharing system. Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed. The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform. A numerical simulation is performed to demonstrate the performance of the formation flight guidance and control system for multiple UAVs. Finally, a flight test is conducted to verify the proposed algorithm for the multi-UAV system.

No MeSH data available.