Flipper Control Method for Tracked Robot Based on Deep Reinforcement Learning

doi:10.16182/j.issn1004731x.joss.22-1105

Abstract

Abstract:

Tracked robots with flippers have certain terrain adaptation capabilities. To improve the intelligent operation level of robots in complex environments, it is significant to realize the flipper autonomously control. Combining the expert experience in obstacle crossing and optimization indicators, Markov decision process(MDP) modeling of the robot's flipper control problem is carried out and a simulation training environment based on physics simulation engine Pymunk is built. A deep reinforcement learning control algorithm based on dueling double DQN(D3QN) network is proposed for controlling the flippers. With terrain information and robot state as the input and the four flippers' angle as the output, the algorithm can achieve the self-learning control of the flippers in challenging terrain. The learned flipper control policy is compared with the manual operation in Gazebo 3D simulation environment. The results show that the proposed algorithm can enable the flippers of robot to obtain adaptive adjustment ability, which helps the robot pass complex terrain more efficiently.

Key words: tracked robot, flipper autonomous control, autonomous traversal, DRL, robot operation

CLC Number:

TP242.6

Pan Hainan, Chen Bailiang, Huang Kaihong, Ren Junkai, Cheng Chuang, Lu Huimin, Zhang Hui. Flipper Control Method for Tracked Robot Based on Deep Reinforcement Learning[J]. Journal of System Simulation, 2024, 36(2): 405-414.

Figures/Tables 15

Fig. 1

Fig. 2

Fig. 3

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Fig. 6

Table 1

Table 2

Parameters of flipper control algorithm

$ξ 1$	$ξ 2$	$ξ 3$	$ξ 4$	$t m a x$	γ	l_r
0.04	0.1	10	3	400	0.96	0.000 5

Table 2

Fig. 7

Fig. 8

Fig. 9

Fig. 10

Table 3

Fig. 11

Table 4

Indicator comparison between manual and our work

指标	人工操作		本文算法
指标	0.4 m 单台阶	陡峭楼梯	0.4 m 单台阶	陡峭楼梯
t_cost/s	46.17	76.53	28.07	41.21
$θ ̂ R$ /rad	4.02	6.30	3.43	4.53
$θ ̂ R, m a x - θ ̂ R, m i n$ /rad	2.92	3.88	1.11	2.60

Table 4

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地形场景	越障类型	台阶高度/m	台阶长度/m	台阶数量	楼梯坡度/(°)
0.4 m单台阶	向上/向下	0.4	3.0	1
陡峭楼梯	向上	0.2	0.3	6	33.7
陡峭楼梯	向下	0.2	0.2	6	45.0

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