Sparse parameter estimation of LTI models with &lt;i&gt;l&lt;SUP align="right"&gt;p&lt;/SUP&gt;&lt;/i&gt; sparsity using genetic algorithm

Saini, Vikram; Dewan, Lillie

doi:10.1504/ijmic.2018.089613

Cited by 3 publications

(1 citation statement)

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“…Comprehensively analyze the research results in the field of robot path planning at home and abroad. The methods commonly used in track planning include A * algorithm, artificial potential field method, ant colony algorithm, genetic algorithm, particle swarm algorithm [3][4][5] etc. Among them, A * algorithm, as the most widely used heuristic search algorithm, has better planning ability in static global planning, but it has weak planning ability in high complexity space or dynamic space.…”

Section: Introductionmentioning

confidence: 99%

Multi-rotor UAV Track Planning Based on Improved Artificial Potential Field

Lee

et al. 2019

Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019)

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An improved artificial potential field (APF) method is proposed to solve the multi-rotor UAV flight path planning problem in this paper. Firstly, the grid method is adopted to build the environment model. After that, the A * algorithm is for generating the global path, and performs optimization for the node on the global path. Finally, the potential function of the traditional APF method is improved that an attraction force made by the global path to the multi-rotor drone is introduced, so the UAV can move guided by both obstacle and target together. Simulation results show that the proposed method can effectively correct the defects and deficiencies of the traditional APF method. The trajectory planning quality of multi-rotor UAVs in static and dynamic environments can be improved with the combination of the global advantages of A * algorithm and the APF method based real-time obstacle avoidance capability.

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Section: Introductionmentioning

confidence: 99%