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Title: Control based motion primitives for quadrotor trajectory generation
Authors: Lai, Shupeng 
Lan, Menglu
Chen, Ben M 
Keywords: Science & Technology
Physical Sciences
Automation & Control Systems
Computer Science, Artificial Intelligence
Engineering, Electrical & Electronic
Operations Research & Management Science
Mathematics, Applied
Computer Science
Motion planning
Trajectory generation
Motion primitives
Unmanned aerial systems
Issue Date: 1-Jan-2019
Publisher: IEEE
Citation: Lai, Shupeng, Lan, Menglu, Chen, Ben M (2019-01-01). Control based motion primitives for quadrotor trajectory generation. 38th Chinese Control Conference (CCC) 2019-July : 8323-8329. ScholarBank@NUS Repository.
Abstract: The local motion planning is critical for the safe operation of an autonomous vehicle such as the quadrotor in which motion primitives are usually adopted to find valid and efficient reaction. We present in this work a method that is capable of generating a class of motion primitives for the quadrotor. Compared to the previous approaches, these primitives are capable of minimizing multiple types of cost functions while satisfying the motion constraints of the quadrotor. Moreover, neural networks are adopted to approximate the generated motions to further boost the online evaluation efficiency. Finally, the local motion planning is achieved through solving a non-convex optimization problem with particle swarm techniques in a receding horizon fashion. The optimization process is a natural extension of the previous tree searching based methods. The proposed approach is computationally efficient and has been tested in a real environment on an actual quadrotor platform.
Source Title: 38th Chinese Control Conference (CCC)
ISBN: 9789881563972
ISSN: 21612927
DOI: 10.23919/ChiCC.2019.8865876
Appears in Collections:Staff Publications

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