Live-fly experimentation for pigeon-inspired obstacle avoidance of quadrotor unmanned aerial vehicles
|
摘要
In this paper, we applied a pigeon-inspired obstacle-avoidance model to the flight of quadrotor UAVs through environments with obstacles. Pigeons bias their flight direction by considering the largest gap and minimum required steering. Owing to the similarities between pigeon flocks and UAV swarms in terms of mission requirements, the pigeon-inspired obstacle-avoidance model is used to control a UAV swarm so that it can fly through a complex environment with multiple obstacles. The simulation and flight results illustrate the viability and superiority of pigeon-inspired obstacle avoidance for quadrotor UAVs.
In this paper, we applied a pigeon-inspired obstacle-avoidance model to the flight of quadrotor UAVs through environments with obstacles. Pigeons bias their flight direction by considering the largest gap and minimum required steering. Owing to the similarities between pigeon flocks and UAV swarms in terms of mission requirements, the pigeon-inspired obstacle-avoidance model is used to control a UAV swarm so that it can fly through a complex environment with multiple obstacles. The simulation and flight results illustrate the viability and superiority of pigeon-inspired obstacle avoidance for quadrotor UAVs.
In this paper, we applied a pigeon-inspired obstacle-avoidance model to the flight of quadrotor UAVs through environments with obstacles. Pigeons bias their flight direction by considering the largest gap and minimum required steering. Owing to the similarities between pigeon flocks and UAV swarms in terms of mission requirements, the pigeon-inspired obstacle-avoidance model is used to control a UAV swarm so that it can fly through a complex environment with multiple obstacles. The simulation and flight results illustrate the viability and superiority of pigeon-inspired obstacle avoidance for quadrotor UAVs.
引文
1 Chen Z Y,Luo X Y,Dai B C.Design of obstacle avoidance system for micro-UAV based on binocular vision.In:Proceedings of International Conference on Industrial Informatics-Computing Technology,Intelligent Technology,Industrial Information Integration,Wuhan,2017.67-70
2 Meng G L,Pan H B.The application of ultrasonic sensor in the obstacle avoidance of quad-rotor UAV.In:Proceedings of Guidance,Navigation and Control Conference,Nanjing,2016.976-981
3 Yang Y,Wang T T,Chen L,et al.Stereo vision based obstacle avoidance strategy for quadcopter UAV.In:Proceedings of Chinese Control and Decision Conference,Shenyang,2018
4 Peng X Z,Lin H Y,Dai J M.Path planning and obstacle avoidance for vision guided quadrotor UAV navigation.In:Proceedings of IEEE International Conference on Control and Automation,Kathmandu,2016.984-989
5 Zhao Y J,Zheng Z,Zhang X Y,et al.Q learning algorithm based UAV path learning and obstacle avoidance approach.In:Proceedings of Chinese Control Conference,Dalian,2017.3397-3402
6 Cekmez U,Ozsiginan M,Sahingoz O K.Multi colony ant optimization for UAV path planning with obstacle avoidance.In:Proceedings of International Conference on Unmanned Aircraft Systems,Arlington,2016.47-52
7 Norberg U M.Vertebrate flight:mechanics,physiology,morphology,ecology and evolution.Comp Biochem Phys Part A-Phy,1990,96:529
8 Qiu H X,Wei C,Dou R,et al.Fully autonomous flying:from collective motion in bird flocks to unmanned aerial vehicle autonomous swarms.Sci China Inf Sci,2015,58:128201
9 Luo Q N,Duan H B.An improved artificial physics approach to multiple UAVs/UGVs heterogeneous coordination.Sci China Technol Sci,2013,56:2473-2479
10 Zhang T J.Unmanned aerial vehicle formation inspired by bird flocking and foraging behavior.Int J Autom Comput,2018,15:402-416
11 Baptista L,Trail P,Horblit H.Family columbidae.In:Handbook of the Birds of the World.Barcelona:Lynx Edicions,1997
12 Lin H T,Ros I G,Biewener A A.Through the eyes of a bird:modelling visually guided obstacle flight.J R Soc Interface,2014,11:20140239
13 Moussaid M,Helbing D,Theraulaz G.How simple rules determine pedestrian behavior and crowd disasters.Proc Natl Acad Sci USA,2011,108:6884-6888
14 Qiu H X,Duan H B.Pigeon interaction mode switch-based UAV distributed flocking control under obstacle environments.ISA Trans,2017,71:93-102
15 Land M F,Collett T S.Chasing behaviour of houseflies(fannia canicularis).J Comp Physiol,1974,89:331-357
16 Warren W H,Fajen B R.Behavioral dynamics of visually guided locomotion.In:Coordination:Neural,Behavioral and Social Dynamics.Berlin:Springer,2008.45-75
17 Foundation O S R.Robot operating system.http://www.ros.org/about-ros/
18 Rokonuzzaman M,Amin M A A,Ahmed M H K M U,et al.Automatic vehicle identification system using machine learning and robot operating system(ROS).In:Proceedings of the 4th International Conference on Advances in Electrical Engineering(ICAEE 2017),Dhaka,2017.253-258
2 Meng G L,Pan H B.The application of ultrasonic sensor in the obstacle avoidance of quad-rotor UAV.In:Proceedings of Guidance,Navigation and Control Conference,Nanjing,2016.976-981
3 Yang Y,Wang T T,Chen L,et al.Stereo vision based obstacle avoidance strategy for quadcopter UAV.In:Proceedings of Chinese Control and Decision Conference,Shenyang,2018
4 Peng X Z,Lin H Y,Dai J M.Path planning and obstacle avoidance for vision guided quadrotor UAV navigation.In:Proceedings of IEEE International Conference on Control and Automation,Kathmandu,2016.984-989
5 Zhao Y J,Zheng Z,Zhang X Y,et al.Q learning algorithm based UAV path learning and obstacle avoidance approach.In:Proceedings of Chinese Control Conference,Dalian,2017.3397-3402
6 Cekmez U,Ozsiginan M,Sahingoz O K.Multi colony ant optimization for UAV path planning with obstacle avoidance.In:Proceedings of International Conference on Unmanned Aircraft Systems,Arlington,2016.47-52
7 Norberg U M.Vertebrate flight:mechanics,physiology,morphology,ecology and evolution.Comp Biochem Phys Part A-Phy,1990,96:529
8 Qiu H X,Wei C,Dou R,et al.Fully autonomous flying:from collective motion in bird flocks to unmanned aerial vehicle autonomous swarms.Sci China Inf Sci,2015,58:128201
9 Luo Q N,Duan H B.An improved artificial physics approach to multiple UAVs/UGVs heterogeneous coordination.Sci China Technol Sci,2013,56:2473-2479
10 Zhang T J.Unmanned aerial vehicle formation inspired by bird flocking and foraging behavior.Int J Autom Comput,2018,15:402-416
11 Baptista L,Trail P,Horblit H.Family columbidae.In:Handbook of the Birds of the World.Barcelona:Lynx Edicions,1997
12 Lin H T,Ros I G,Biewener A A.Through the eyes of a bird:modelling visually guided obstacle flight.J R Soc Interface,2014,11:20140239
13 Moussaid M,Helbing D,Theraulaz G.How simple rules determine pedestrian behavior and crowd disasters.Proc Natl Acad Sci USA,2011,108:6884-6888
14 Qiu H X,Duan H B.Pigeon interaction mode switch-based UAV distributed flocking control under obstacle environments.ISA Trans,2017,71:93-102
15 Land M F,Collett T S.Chasing behaviour of houseflies(fannia canicularis).J Comp Physiol,1974,89:331-357
16 Warren W H,Fajen B R.Behavioral dynamics of visually guided locomotion.In:Coordination:Neural,Behavioral and Social Dynamics.Berlin:Springer,2008.45-75
17 Foundation O S R.Robot operating system.http://www.ros.org/about-ros/
18 Rokonuzzaman M,Amin M A A,Ahmed M H K M U,et al.Automatic vehicle identification system using machine learning and robot operating system(ROS).In:Proceedings of the 4th International Conference on Advances in Electrical Engineering(ICAEE 2017),Dhaka,2017.253-258