Multi-objective time-energy-impact optimization for robotic excavator trajectory planning

Single-objective optimal trajectory cannot adapt to the complex requirements of excavator construction. A comprehensive optimal trajectory planning method is proposed to optimize the working time, energy consumption, and operational impact of robotic excavators. Without fusing any performance indexe...

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Vydané v:Automation in construction Ročník 156; s. 105094
Hlavní autori: Feng, Hao, Jiang, Jinye, Ding, Nan, Shen, Fangping, Yin, Chenbo, Cao, Donghui, Li, Chunbiao, Liu, Tao, Xie, Jiaxue
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 01.12.2023
Predmet:
Excavator
Hydraulic system
Particle swarm optimization algorithm
Trajectory planning
Excavator
Trajectory planning
Hydraulic system
Particle swarm optimization algorithm
ISSN:0926-5805, 1872-7891
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Popis
Shrnutí:Single-objective optimal trajectory cannot adapt to the complex requirements of excavator construction. A comprehensive optimal trajectory planning method is proposed to optimize the working time, energy consumption, and operational impact of robotic excavators. Without fusing any performance indexes, a normalized multi-objective function and an improved particle swarm optimization algorithm are established to achieve a comprehensive optimization of multiple objectives, while considering joint angle, velocity, acceleration, and quadratic acceleration constraints. Typical deep pit excavation simulation and experimental results show that the multi-objective optimization method is feasible, can balance multi-objective constraints, and can avoid falling into extremely long working times or large impacts. This method offers a more efficient and effective solution for multi-objective trajectory planning and provides a method for planning excavation trajectories based on different operating scenarios and objectives. •Working time, energy consumption and operation impact are considered in trajectory planning.•A normalized multi-objective function is established to achieve a comprehensive optimization.•An improved particle swarm optimization algorithm is proposed to obtain the optimal solution.•Effectiveness of the trajectory planning method is validated by simulations and experiments.•The multi-objective optimization method can meet the actual construction requirements.
ISSN:0926-5805
1872-7891
DOI:10.1016/j.autcon.2023.105094