Learning and Generalization of Dual-Robot Cooperative Handling Trajectory Based on Dynamic Movement Primitives

doi:10.12141/j.issn.1000-565X.230013

Abstract

Abstract:

Aiming at the problems of complex trajectory learning and lack of coordination constraint analysis when a dual-robot collaborative system performs humanoid tasks with strong coordination constraints, this paper proposed a dual-robot cooperative handling trajectory learning and generalization method based on dynamic movement primitives (DMPs). Firstly, starting from the dual-robot cooperative handling task, the coordination constraints of the dual-robot were analyzed, and the motion constraint model of the dual-robot was established. Then, the robot motion trajectory was decoupled into position trajectory and orientation trajectory, and the quaternion was used to realize the non-singular description of the orientation trajectory. And the dynamic movement primitives model of position trajectory and orientation trajectory were established respectively. They were combined with the dual robot motion constraint model and DMPs model, and the dual-robot movement trajectory was obtained, taking into account their respective task requirements and relative pose constraints. Finally, the simulation and experiments of the cooperative handling trajectory of the two robots were carried out. The results show that: using the learning and generalization method of the dual-robot cooperative handling trajectory, when the starting and ending states are changed, the position errors of start point and end point of the dual-robot cooperative handling with the fixed orientation are 0.029 2 mm and 0.112 7 mm respectively; the position errors of start point and end point of variable orientation coordinated handling are 0.032 3 mm and 0.113 1 mm respectively; and the quaternion orientation errors of the end point are 0.001 4, 0.002 7, 0.001 8, 0.003 0, indicating that the cooperative handling trajectory learning and generalization method has high motion control accuracy; even if the task parameters of the starting and ending are changed, the generalized trajectory can still ensure the accessibility of the target, which verified the scientificity and effectiveness of the proposed dual-robot coordination motion trajectory control strategy. The method proposed in this paper can effectively learn the human handling process and can accurately generalize new motion trajectories. It realizes the dual-robot coordinated motion and has important engineering application value.

Key words: dynamic movement primitive, dual-robot collaboration, trajectory learning, coordination constraint, quaternion

CLC Number:

TP242.2

CAO Xuepeng, WANG Deshuo, FENG Yanli, et al. Learning and Generalization of Dual-Robot Cooperative Handling Trajectory Based on Dynamic Movement Primitives[J]. Journal of South China University of Technology(Natural Science Edition), 2023, 51(12): 9-20.

Figures/Tables 18

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Table 1

Mximum target position error of 3D trajectory learning and generalization"

轨迹形式	$Δ x, Δ y, Δ z$	空间误差 $ε$
仅改变起点	0.008 5，0.007 9，0.008 8	0.014 6
仅改变终点	0.005 6，0.005 6，0.007 3	0.010 8
起、终点均改变	0.012 1，0.009 4，0.012 6	0.019 8

Table 1

Fig.6

Fig.7

Fig.8

Table 2

Fig.9

Fig.10

Fig.11

Fig.12

Table 3

Errors of initial-target position of the handling experiment with fixed orientation"

参数	$Δ x$ /mm	$Δ y$ /mm	$Δ z$ /mm
起点误差	0.017	0.021	0.011
终点误差	0.044	0.095	0.039

Table 3

Fig.13

Fig.14

Table 4

Deviations of initial-target state of the handling experiment with variable orientation"

参数	$Δ x$ /mm	$Δ y$ /mm	$Δ z$ /mm	$Δ q w$	$Δ q x$	$Δ q y$	$Δ q z$
起点误差	0.022	0.019	0.014	0.000 3	0.000 6	0.001 1	0.000 4
终点误差	0.025	0.102	0.042	0.001 4	0.002 7	0.001 8	0.003 0

Table 4

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参数	x/mm	y/mm	z/mm	q_w	q_x	q_y	q_z
初始状态	-250	-310	200	0.959 7	0.176 8	0.128 4	-0.176 8
目标状态	-310	270	270	0.498 2	0.613 8	0.135 2	-0.597 9

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