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Volumn 9, Issue 1, 2017, Pages

Unmanned aerial vehicle flight point classification algorithm based on symmetric big data

Author keywords

Demonstration based learning; K means algorithm; Unmanned aerial vehicle

Indexed keywords


EID: 85011664460     PISSN: None     EISSN: 20738994     Source Type: Journal    
DOI: 10.3390/sym9010001     Document Type: Article
Times cited : (10)

References (18)
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    • Kim, D.1    Hong, S.K.2
  • 6
    • 85011669284 scopus 로고    scopus 로고
    • Structure design of surveillance location-based UAV motor primitives
    • Kwak, J.; Sung, Y. Structure design of surveillance location-based UAV motor primitives. Korea Inf. Process. Soc. Trans. Softw. Data Eng. 2016, 5, 181-186.
    • (2016) Korea Inf. Process. Soc. Trans. Softw. Data Eng , vol.5 , pp. 181-186
    • Kwak, J.1    Sung, Y.2
  • 8
    • 84965126887 scopus 로고    scopus 로고
    • An automatic flight control system for the AR.Drone Quadrotor in outdoor environments
    • Education and Development of Unmanned Aerial Systems (RED-UAS), Cancun, Mexico, 23-24 November
    • Santana, L.V.; Brandao, A.S.; Sarcinelli-Filho, M. An automatic flight control system for the AR.Drone Quadrotor in outdoor environments. In Proceedings of the 2015 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS), Cancun, Mexico, 23-24 November 2015; pp. 401-410.
    • (2015) Proceedings of the 2015 Workshop on Research , pp. 401-410
    • Santana, L.V.1    Brandao, A.S.2    Sarcinelli-Filho, M.3
  • 9
    • 85011698918 scopus 로고    scopus 로고
    • A study on the algorithm for automatic generation of optimal waypoint with terrain avoidance
    • Park, J.; Park, S.; Ryoo, C.; Shin, S. A study on the algorithm for automatic generation of optimal waypoint with terrain avoidance. J. Korean Soc. Aeronaut. Space Sci. 2009, 37, 1104-1111.
    • (2009) J. Korean Soc. Aeronaut. Space Sci , vol.37 , pp. 1104-1111
    • Park, J.1    Park, S.2    Ryoo, C.3    Shin, S.4
  • 13
    • 0033204902 scopus 로고    scopus 로고
    • An empirical comparison of four initialization methods for the K-means algorithm
    • Pena, J.M.; Lozano, J.A.; Larranaga, P. An empirical comparison of four initialization methods for the K-means algorithm. Pattern Recognit. Lett. 1999, 20, 1027-1040.
    • (1999) Pattern Recognit. Lett , vol.20 , pp. 1027-1040
    • Pena, J.M.1    Lozano, J.A.2    Larranaga, P.3
  • 15
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    • Natural methods for robot task learning: instructive demonstrations, generalization and practice
    • Melbourne, Victoria, Australia, 14-18 July 2003; ACM Press: New York, NY, USA
    • Nicolescu, M.N.; Mataric, M.J. Natural methods for robot task learning: instructive demonstrations, generalization and practice. In Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, Melbourne, Victoria, Australia, 14-18 July 2003; ACM Press: New York, NY, USA, 2003; pp. 241-248.
    • (2003) Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems , pp. 241-248
    • Nicolescu, M.N.1    Mataric, M.J.2
  • 16
    • 85011695704 scopus 로고    scopus 로고
    • Graph-based motor primitive generation framework: UAV motor primitives by demonstration-based learning
    • Sung, Y.; Kwak, J.; Park, J.H. Graph-based motor primitive generation framework: UAV motor primitives by demonstration-based learning. Hum. Cent. Comput. Inf. Sci. 2015, 35, 509-510.
    • (2015) Hum. Cent. Comput. Inf. Sci , vol.35 , pp. 509-510
    • Sung, Y.1    Kwak, J.2    Park, J.H.3
  • 17
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    • (accessed on 26 September 2016)
    • Parrot AR.Drone 2.0. Available online: https://www.parrot.com/us/drones/parrot-ardrone-20-gps-edition (accessed on 26 September 2016).


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.