Strike Strategy Planning Method of Unmanned Ground Vehicles Based on Improved PPO Algorithm

doi:10.16182/j.issn1004731x.joss.25-0486

Abstract

Abstract:

An improved PPO algorithm based on the hybrid action space and gated recurrent unit (GRU) is proposed to address the limitations of predefined strike rules in maximizing the hitting accuracy of unmanned ground vehicles and the difficult coupling and optimization of continuous motion planning and discrete strike decision-making. The environmental model and target model are built for the process of unmanned ground vehicles' strike missions, coupled with a three-layer model for unmanned ground vehicles that fuses kinematic constraints, situational awareness, and dynamic decision-making. Two distinct policy networks are employed, including the continuous motion planning network for path planning, and the discrete strike decision-making network for solving the strike decision-making problems in the process of strike location and target sequence selection. A GRU module is introduced to address the partially observable nature of the environment by inferring current states from historical observations. The simulation results show that this method can couple and optimize the path planning and strike decision-making of unmanned ground vehicles, improving the ability of unmanned ground vehicles to autonomously perform strike missions.

Key words: DRL, unmanned ground vehicle, path planning, strike decision-making, PPO

CLC Number:

TP391.9

Wang Bingkun, Wang Yue, Yang Mei, Zhang Pengnian, Fan Bohao, Tang Jie. Strike Strategy Planning Method of Unmanned Ground Vehicles Based on Improved PPO Algorithm[J]. Journal of System Simulation, 2026, 38(2): 372-386.

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参数	值	参数	值
截断比率	0.2	训练周期	200
每轮更新频率	20	回合交互数	100
折扣率	0.99	熵	0.02
学习率	0.000 1	批量大小	32

指标	Hybrid-PPO	GRU-PPO	改进PPO
平均奖励	2.133	2.103	3.105
收敛阶段平均奖励	2.105	2.108	3.217
标准差	0.539	0.277	0.363
收敛阶段标准差	0.669	0.251	0.169

指标	Hybrid-PPO	GRU-PPO	改进PPO
平均损失	0.726	0.330	0.178
收敛阶段平均损失	0.915	0.197	0.084
标准差	3.579	0.692	0.293
收敛阶段标准差	6.027	0.281	0.089

指标	Hybrid-PPO	GRU-PPO	改进PPO
平均命中率	0.502 5	0.682 5	0.667 5
平均威胁度	0.326 7	0.363 4	0.396 7
行驶距离/km	0.692 0	2.959 0	1.945 0