Design of Fully Automatic Drone Parachute System with Temperature Compensation Mechanism for Civilian and Military Applications

Application of Unmanned Aerial Vehicles (a.k.a. drones) is becoming more popular and their safety is becoming a serious concern. Due to high cost of top-end drones and requirements for secure landing, development of reliable drone recovery systems is a hot topic now. In this paper, we describe the development of a parachute system with fall detection based on accelerometer-gyroscope MPU – 6050 and fall detection algorithm based on the Kalman filter to reduce acceleration errors while drone is flying. We developed the compensation algorithm for temperature-related accelerometer errors. The parachute system tests were performed from a small height on a soft surface. Later, the system was tested under real-world conditions. The system functioned effectively, resulting in parachute activation times of less than 0.5s. We also discuss the civilian and military applications of the developed recovery system in harsh (high temperature) environment.

[1]  Mark A. Minor,et al.  UAV fall detection from a dynamic perch using Instantaneous Centers of Rotation and inertial sensing , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[2]  Inhan Kim,et al.  Prediction of the parachute deploy for landing at the desired point , 2012, 2012 Proceedings of SICE Annual Conference (SICE).

[3]  Douglas J. Krause,et al.  A small unmanned aerial system for estimating abundance and size of Antarctic predators , 2015, Polar Biology.

[4]  Noor Yasmin Zainun,et al.  The Use of UAV in Housing Renovation Identification: A Case Study at Taman Manis 2 , 2018 .

[5]  Klaus Schilling,et al.  Risk Assessment of Flight Paths for Automatic Emergency Parachute Deployment in UAVs , 2015 .

[6]  Alessandro Gardi,et al.  A Unified Analytical Framework for Aircraft Separation Assurance and UAS Sense-and-Avoid , 2018, J. Intell. Robotic Syst..

[7]  Federico Cuesta,et al.  A New Blondin System for Surveying and Photogrammetry , 2013, Sensors.

[8]  Cory Sudduth.  Design of a hybrid rocket / inflatable wing UAV , 2012 .

[9]  Qingbin Zhang,et al.  Parachute dynamics and perturbation analysis of precision airdrop system , 2016 .

[10]  Ying Wu,et al.  Development of an UAS for post-earthquake disaster surveying and its application in Ms7.0 Lushan Earthquake, Sichuan, China , 2014, Comput. Geosci..

[11]  Kun Ming Du.  Simulation Analysis on the Problem of Opening Main Parachute Used in UAV Recovery System , 2013 .

[12]  Liu Li,et al.  Parachute Decelerate Trajectory Optimization Design Based on Genetic Algorithm , 2009, 2009 International Workshop on Intelligent Systems and Applications.

[13]  Bar-Ilan University,et al.  Device for Detection of Fuselage Defective Parts , 2013 .

[14]  Jing Luo,et al.  Fall Monitoring Device for Old People based on Tri-Axial Accelerometer , 2015 .

[15]  Vladimir Dobrokhodov,et al.  Six-Degree-of-Freedom Model of a Controlled Circular Parachute , 2002 .

[16]  Irene Marzolff,et al.  Unmanned Aerial Vehicle (UAV) for Monitoring Soil Erosion in Morocco , 2012, Remote. Sens..

[17]  Lih Shyng Shyu,et al.  Mini UAV Design and Manufacture with Bungee Launched / Parachute Recovery , 2014 .

[18]  Rytis Maskeliunas,et al.  Block Matching Based Obstacle Avoidance for Unmanned Aerial Vehicle , 2018, ICAISC.

[19]  Kirk Graham Stewart Cartwright.  Feasibility of Parachute Recovery Systems for Small UAVs , 2009 .

[20]  Chung-Kiak Poh,et al.  Radio Controlled “3D Aerobatic Airplanes” as Basis for Fixed-Wing UAVs with VTOL Capability , 2014 .

[21]  Chen Jian-ping.  Dynamic Analysis for Parachute Recovery System of Unmanned Aerial Vehicle , 2012 .

[22]  W. J. Crowther,et al.  Post Stall Landing for Field Retrieval of UAVs , 2007 .

[23]  Chengfu Wu,et al.  Research on Key Problems in Assigned-Point Recovery of UAV Using Parachute , 2012 .

[24]  Karl-Friedrich Doherr,et al.  Nine-Degree-of-Freedom Simulation of Rotating Parachute Systems. , 1992 .

[25]  C. Hugenholtz,et al.  Remote sensing of the environment with small unmanned aircraft systems ( UASs ) , part 1 : a review of progress and challenges 1 , 2014 .

[26]  Giorgio Guglieri.  Parachute-Payload System Flight Dynamics and Trajectory Simulation , 2012 .

[27]  E. H. K. Fung,et al.  Intelligent Automatic Fault Detection for Actuator Failures in Aircraft , 2009, IEEE Transactions on Industrial Informatics.

[28]  L. Tang,et al.  Drone remote sensing for forestry research and practices , 2015, Journal of Forestry Research.

[29]  Kevin M. Passino,et al.  Expert supervision of fuzzy learning systems for fault tolerant aircraft control , 1995 .

[30]  Sang-Hoon Kim,et al.  Fall-Detection Algorithm Using 3-Axis Acceleration: Combination with Simple Threshold and Hidden Markov Model , 2014, J. Appl. Math..

[31]  Weiguo Hu,et al.  Freestanding Flag-Type Triboelectric Nanogenerator for Harvesting High-Altitude Wind Energy from Arbitrary Directions. , 2016, ACS nano.

[32]  S Khantsis,et al.  Control system design using evolutionary algorithms for autonomous shipboard recovery of unmanned aerial vehicles , 2006 .

[33]  Kurt Seifert,et al.  Freescale Semiconductor Application Note Implementing Positioning Algorithms Using Accelerometers by : , 2004 .

[34]  Graham Wild,et al.  Exploring Civil Drone Accidents and Incidents to Help Prevent Potential Air Disasters , 2016 .

[35]  Marisol Gutierrez,et al.  Use of Drones for Surveillance and Reconnaissance of Military Areas , 2018 .

[36]  Ahmad Sedaghat,et al.  Shape and Orifice Optimization of Airbag Systems for UAV Parachute Landing , 2014 .

[37]  Vasile Prisacariu,et al.  RECOVERY SYSTEM OF THE MULTI-HELICOPTER UAV , 2016 .

[38]  Tim Wyllie.  Parachute recovery for UAV systems , 2001 .

[39]  Eleni I. Vlahogianni,et al.  Unmanned Aerial Aircraft Systems for Transportation Engineering: Current Practice and Future Challenges , 2016 .

[40]  Heikki Saari,et al.  Processing and Assessment of Spectrometric, Stereoscopic Imagery Collected Using a Lightweight UAV Spectral Camera for Precision Agriculture , 2013, Remote. Sens..

[41]  Brett C. Eaton,et al.  Remote sensing of the environment with small unmanned aircraft systems (UASs), part 2: scientific and commercial applications , 2014 .

[42]  Rudolph van der Merwe,et al.  The unscented Kalman filter for nonlinear estimation , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[43]  Udo B. Carl,et al.  Redundancy management of fault tolerant aircraft system architectures – reliability synthesis and analysis of degraded system states , 2005 .

[44]  WhiteheadKen,et al.  Remote sensing of the environment with small unmanned aircraft systems (UASs), part 1: a review of progress and challenges1 , 2014 .

[45]  Edward H. Teets,et al.  Atmospheric considerations for uninhabited aerial vehicle (UAV) flight test planning , 1998 .

[46]  L. Johnson,et al.  Nighttime UAV Vineyard Mission: Challenges of See-and-Avoid in the NAS , 2004 .