Path Replanning of Multi-speed Unmanned Tracked Platforms Based on Topological Road Network

doi:10.12382/bgxb.2021.0827

Abstract

Abstract:

To solve the problem of poor robustness and weak scene adaptability of replanning for unmanned tracked hybrid platforms in the off-road environment, a method that incorporates a multi-objective function model and uses a three-order spiral of multi-stage sampling optimization to reconstruct the planned path is proposed. This method regenerates a reference trajectory that can reach the target when no local path is found in dynamic driving. It focuses on solving the cost optimization problem during the back-off road driving of a unmanned tracked platform. The platform is also equipped with a two-speed planetary automatic mechanical transmission. The unmanned platform can switch to different gears according to the driving speed during the traveling process to meet the speed requirements under different road conditions, and thus it has high adaptability. The real vehicle platform verifies that the method proposed in this study can be used for different off-road scenarios. According to the objective cost function model of the three parameters of travel time, energy consumption, and number of shifts, the best replanning strategy can be obtained, as well as an optimal and passable route. The results show that the path replanning method reduces the time and energy costs of the planning process. The appropriate gear is selected while both time and energy, different turning radiuses and speeds are considered. Thus, the longitudinal movement performance, effectiveness, and economy of the platform are guaranteed.

Key words: unmanned tracked hybrid platform, off-road, automatic shift, replanning, three-order spiral

CLC Number:

TJ810.2

LIU Longlong, CHEN Huiyan, LIU Hai’ou, GUAN Haijie, LU Jiaxing. Path Replanning of Multi-speed Unmanned Tracked Platforms Based on Topological Road Network[J]. Acta Armamentarii, 2023, 44(1): 279-289.

Figures/Tables 17

Fig.1 Dynamic model of the platform

Fig.2 Single-sided structure of the platform-driven system

Table 1 Parameters of the unmanned tracked platform system

参数	数值
长L×宽W×高H/mm	5476×2978×1800
质量m/kg	9360
电机峰值功率/kW	110
电机峰值转矩/(N·m)	800
电机持续转矩/(N·m)	500
i₀	5.5
i_g	2.7/1
r/mm	265

Fig.3 Global bidirectional diagram

Fig.4 Replanning scenario when roads are blocked

Fig.5 Block diagram of the replanning triggering module

Table 2 Parameters of the replanning triggering process

参数	数值
l/m	40
D_h/m	8
N/次	20
D_m/m	5
T_wait/s	3

Fig.6 Flow chart of replanning triggering

Fig.7 Topological relationship interruption strategy in replanning inreplanning

Table 3 Entropy method assignment results

子目标参数	熵权e_j	重要性比r_j	权重v_j
P₁	0.9557	1.0441	0.32
P₂	0.9978	1.0000	0.55
P₃	0.9435	1.0129	0.13

Fig.8 Test platform with subsystems

Fig.9 Satellite image of the test site

Fig.10 Replanning triggered and executed

Fig.11 Comparison of single-target results for different road sections

Fig.12 Results of path replanning using single parameter

Fig.13 Replanning path using multiple parameters

Table 4 Results of the entropy method for different roads

路段	时间/s	能量/%	换挡次数	综合结果
路段1	278	2.65	3	0.8104
路段2	341	2.42	3	0.8295
路段3	300	3.50	2	0.9187
路段4	309	2.53	2	0.7743

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