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Çok Rotorlu İHA için Önerilen Uyarlanabilir İniş Takımının Tasarımı ve Kinematik Analizi

Yıl 2022, Cilt: 9 Sayı: 1, 159 - 170, 31.01.2022
https://doi.org/10.31202/ecjse.952728

Öz

Çok rotorlu insansız hava araçlarının (İHA) veya dikey olarak kalkış ve iniş yapabilen hava araçlarının en zayıf yönlerinden biri güvenli bir iniş gerçekleştirebilmeleri için düz bir zemine ihtiyaç duymalarıdır. Bu zayıflığın etkisini azaltmak için İHA'ya iniş kabiliyeti ile ilgili bazı ek beceriler kazandıracak sistemlerin eklenmesi kaçınılmazdır. Bu çalışmada, çok rotorlu bir İHA için dört kollu adaptif iniş takımı tasarlanmış ve kinematik analizi yapılmıştır. Uyarlanabilirlik özelliği, aracın engebeli zemine güvenli bir şekilde inebilmesi için, dönel olan eklemlerin açıları otomatik olarak değiştirilerek kol uçları engebeli zemine göre konumlanmasıyla elde edilir. Her biri iki eklemli olan dört robotik koldan oluşan adaptif iniş takımının eklem açıları, ultrasonik mesafe sensöründen alınan mesafe bilgisine bağlı olarak kontrolcü tarafından değiştirilir. Bu mesafe bilgisi, belirlenen algoritmaya göre kontrolörde değerlendirilerek eklemlerin gerekli açı değerleri belirlenir. Bu çalışma kapsamında, matematiksel modeli de elde dilen sekiz rotorlu İHA'ya uygun olarak ölçeklendirilmiş adaptif iniş takımı tasarlanmıştır. Her birinin uzunluğu 200 mm olan ikişer uzuvlu dört koldan oluşan bu iniş takımına göre İHA'nın güvenli bir şekilde inebileceği engebeli zeminin maksimum eğim açısı 44.5° olarak hesaplanmıştır. Bunun yanında, gerçekleştirilen simülasyonla kol uç noktasının, ki bu kolun zemine temas edecek kısmı, hareket yörüngesi elde edilmiştir.

Kaynakça

  • Ahirwar, S., Swarnkar, R., Bhukya, S., Namwade, G., Application of Drone in Agriculture, Int. J. Curr. Microbiol. Appl. Sci., 2019, 8 (1) 2500–2505.
  • Wu, K., Rodriguez, G.A., Zajc, M., Jacquemin, E., Clément, M., De Coster, A., Lambot, S., A New Drone-Borne GPR for Soil Moisture Mapping, Remote Sens. Environ., 2019, 235, 111456.
  • Liu, Y., Noguchi, N., Okamoto, H., Ishii, K., Development of A Small-Sized and Low-Cost Attitude Measurement Unit for Agricultural Robot Application, Tarim Bilim. Derg., 2018, 24 (1), 33–41.
  • Liu, S., Dong, W., Ma, Z., Sheng, X., Adaptive Aerial Grasping and Perching with Dual Elasticity Combined Suction Cup, IEEE Robot. Autom. Lett., 2020, 5 (3), 4766–4773. Villa, D.K.D., Brandão, A.S., Sarcinelli-Filho, M., A Survey on Load Transportation Using Multirotor UAVs, J. Intell. Robot. Syst. Theory Appl., 2020, 98, 267–296.
  • Bonyan Khamseh, H., Janabi-Sharifi, F., Abdessameud, A., Aerial manipulation—A literature Survey, Rob. Auton. Syst., 2018, 107, 221–235.
  • Ribeiro, M., Ferreira, A.S., Goncalves, P., Galante, J., de Sousa, J.B., Quadcopter Platforms for Water Sampling and Sensor Deployment, in: Ocean., 2016 MTS/IEEE Monterey, IEEE, 2016, 1–5.
  • Şen, M.A., Bakırcıoğlu, V., Kalyoncu, M., Inverse Kinematic Analysis Of A Quadruped Robot, Int. J. Sci. Technol. Res., 2017, 6 (09) 285–289.
  • Yıldırım, Ş., Arslan, E., A Comparison of Six Legged ODE (Open Dynamics Engine) Based Gait control Algorithm and Standard Walking Gaits, Avrupa Bilim ve Teknoloji Dergisi , Özel Sayı, 2019, 242-255.
  • Ersin, Ç., Yaz, M., Gökçe, H., Upper Limb Robot Arm System Design and Kinematic Analysis, El-Cezeri J. Sci. Eng., 2020, 7 (3) 1320–1331.
  • DARPA, Robotic Landing Gear Could Enable Future Helicopters to Take Off and Land Almost Anywhere, 2015. [https://www.darpa.mil/news-events/2015-09-10 (accessed June 7, 2021)].
  • Sarkisov, Y.S., Yashin, G.A., Tsykunov, E. V., Tsetserukou, D., DroneGear: A Novel Robotic Landing Gear with Embedded Optical Torque Sensors for Safe Multicopter Landing on an Uneven Surface, IEEE Robot. Autom. Lett., 2018, 3 (3) 1912–1917.
  • Luo, C., Zhao, W., Du, Z., Yu, L., A Neural Network Based Landing Method for an Unmanned Aerial Vehicle with Soft Landing Gears, Appl. Sci., 2019, 9 (15), 2976.
  • Çabuk, N., Bakırcıoğlu, V., Artificial Neural Networks Based Inverse Kinematics Solution and Simulation of a Six Degree of Freedom Lighting Manipulator, Gazi Univ. J. Sci. Part C Des. Technol., 2018, 6 (1) 117–125.
  • Yildirim, Ş., Design of a Proposed Neural Network Control System for Trajectory Controlling of Walking Robots, Simul. Model. Pract. Theory., 2008, 16 (3) 368–378.
  • Nadan, P.M., Anthony, T.M., Michael, D.M., Pflueger, J.B., Sethi, M.S., Shimazu, K.N., Tieu, M., Lee, C.L., A Bird-Inspired Perching Landing Gear System, J. Mech. Robot., 2019, 11 (6), 061002.
  • Tang, H., Zhang, D., Gan, Z., Control System for Vertical Take‐Off and Landing Vehicle’s Adaptive Landing Based on Multi‐Sensor Data Fusion, Sensors (Switzerland)., 2020, 20 (16) 1–21.

Design and Kinematic Analysis of Proposed Adaptive Landing Gear for Multirotor UAV

Yıl 2022, Cilt: 9 Sayı: 1, 159 - 170, 31.01.2022
https://doi.org/10.31202/ecjse.952728

Öz

One of the weaknesses of multi-rotor unmanned aerial vehicles (UAVs) or vertical take-off and landing aircraft is that they need a flat surface to make a safe landing. In order to reduce the impact of this weakness, it is inevitable to add systems that will give the UAV some additional capabilities related to landing capability. In this study, a four-arm adaptive landing gear is designed and kinematically analyzed for a multi-rotor UAV. The adaptability feature is achieved by positioning the arm ends relative to the uneven ground by automatically changing the angles of the revolute joints so that the vehicle can land safely on uneven ground. The joint angles of the adaptive landing gear, which consists of four robotic arms, each with two joints, are changed by the controller depending on the distance information received from the ultrasonic distance sensor. This distance information is evaluated in the controller according to the determined algorithm and the required angle values of the joints are determined. Within the scope of this study, a scaled adaptive landing gear was designed for an eight-rotor UAV whose mathematical model was also obtained. According to proposed landing gear, which consists of four arms with two limbs, each with a length of 200 mm, the maximum angle of inclination of the uneven ground on which the UAV can land safely is calculated as 44.5°. In addition, the motion trajectory of the end point of the arm, which is the part of the arm that will contact the ground, was obtained with the simulation performed.

Kaynakça

  • Ahirwar, S., Swarnkar, R., Bhukya, S., Namwade, G., Application of Drone in Agriculture, Int. J. Curr. Microbiol. Appl. Sci., 2019, 8 (1) 2500–2505.
  • Wu, K., Rodriguez, G.A., Zajc, M., Jacquemin, E., Clément, M., De Coster, A., Lambot, S., A New Drone-Borne GPR for Soil Moisture Mapping, Remote Sens. Environ., 2019, 235, 111456.
  • Liu, Y., Noguchi, N., Okamoto, H., Ishii, K., Development of A Small-Sized and Low-Cost Attitude Measurement Unit for Agricultural Robot Application, Tarim Bilim. Derg., 2018, 24 (1), 33–41.
  • Liu, S., Dong, W., Ma, Z., Sheng, X., Adaptive Aerial Grasping and Perching with Dual Elasticity Combined Suction Cup, IEEE Robot. Autom. Lett., 2020, 5 (3), 4766–4773. Villa, D.K.D., Brandão, A.S., Sarcinelli-Filho, M., A Survey on Load Transportation Using Multirotor UAVs, J. Intell. Robot. Syst. Theory Appl., 2020, 98, 267–296.
  • Bonyan Khamseh, H., Janabi-Sharifi, F., Abdessameud, A., Aerial manipulation—A literature Survey, Rob. Auton. Syst., 2018, 107, 221–235.
  • Ribeiro, M., Ferreira, A.S., Goncalves, P., Galante, J., de Sousa, J.B., Quadcopter Platforms for Water Sampling and Sensor Deployment, in: Ocean., 2016 MTS/IEEE Monterey, IEEE, 2016, 1–5.
  • Şen, M.A., Bakırcıoğlu, V., Kalyoncu, M., Inverse Kinematic Analysis Of A Quadruped Robot, Int. J. Sci. Technol. Res., 2017, 6 (09) 285–289.
  • Yıldırım, Ş., Arslan, E., A Comparison of Six Legged ODE (Open Dynamics Engine) Based Gait control Algorithm and Standard Walking Gaits, Avrupa Bilim ve Teknoloji Dergisi , Özel Sayı, 2019, 242-255.
  • Ersin, Ç., Yaz, M., Gökçe, H., Upper Limb Robot Arm System Design and Kinematic Analysis, El-Cezeri J. Sci. Eng., 2020, 7 (3) 1320–1331.
  • DARPA, Robotic Landing Gear Could Enable Future Helicopters to Take Off and Land Almost Anywhere, 2015. [https://www.darpa.mil/news-events/2015-09-10 (accessed June 7, 2021)].
  • Sarkisov, Y.S., Yashin, G.A., Tsykunov, E. V., Tsetserukou, D., DroneGear: A Novel Robotic Landing Gear with Embedded Optical Torque Sensors for Safe Multicopter Landing on an Uneven Surface, IEEE Robot. Autom. Lett., 2018, 3 (3) 1912–1917.
  • Luo, C., Zhao, W., Du, Z., Yu, L., A Neural Network Based Landing Method for an Unmanned Aerial Vehicle with Soft Landing Gears, Appl. Sci., 2019, 9 (15), 2976.
  • Çabuk, N., Bakırcıoğlu, V., Artificial Neural Networks Based Inverse Kinematics Solution and Simulation of a Six Degree of Freedom Lighting Manipulator, Gazi Univ. J. Sci. Part C Des. Technol., 2018, 6 (1) 117–125.
  • Yildirim, Ş., Design of a Proposed Neural Network Control System for Trajectory Controlling of Walking Robots, Simul. Model. Pract. Theory., 2008, 16 (3) 368–378.
  • Nadan, P.M., Anthony, T.M., Michael, D.M., Pflueger, J.B., Sethi, M.S., Shimazu, K.N., Tieu, M., Lee, C.L., A Bird-Inspired Perching Landing Gear System, J. Mech. Robot., 2019, 11 (6), 061002.
  • Tang, H., Zhang, D., Gan, Z., Control System for Vertical Take‐Off and Landing Vehicle’s Adaptive Landing Based on Multi‐Sensor Data Fusion, Sensors (Switzerland)., 2020, 20 (16) 1–21.
Toplam 16 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Nihat Çabuk 0000-0002-3668-7591

Yayımlanma Tarihi 31 Ocak 2022
Gönderilme Tarihi 15 Haziran 2021
Kabul Tarihi 22 Aralık 2021
Yayımlandığı Sayı Yıl 2022 Cilt: 9 Sayı: 1

Kaynak Göster

IEEE N. Çabuk, “Design and Kinematic Analysis of Proposed Adaptive Landing Gear for Multirotor UAV”, ECJSE, c. 9, sy. 1, ss. 159–170, 2022, doi: 10.31202/ecjse.952728.