An Improved Cat Swarm Optimization for Heterogeneous Multiple Mobile Robots

doi:10.16182/j.issn1004731x.joss.23-0783

Abstract

Abstract:

At present, it is difficult to achieve the real homogeneity of the members of the multiple mobile robots. The existing swarm intelligence algorithm is also difficult to accommodate the heterogeneity of the team. Focusing on the heterogeneous cooperation of multiple mobile robots, the concept of mother and child robots is proposed. In order to realize the application of swarm intelligence algorithm in heterogeneous multiple mobile robots, the basic cat swarm algorithm is improved. The sub-domain and neighborhood of cat swarm are defined, and eight improvements of cat swarm algorithm are proposed, including priority of search direction, extended trajectory tracking of robot, attraction of search space and candidate search area. The experimental results show that the concept of mother-child robot can realize the target search of heterogeneous multiple mobile robots, and can contain the heterogeneity of team members and verify the applicability and effectiveness of the improved cat swarm algorithm.

Key words: multiple mobile robots, cat swarm optimization, heterogeneous, sub-domain, search direction

CLC Number:

TP18

Kang Liang, Du Yi, Yin Lihua. An Improved Cat Swarm Optimization for Heterogeneous Multiple Mobile Robots[J]. Journal of System Simulation, 2024, 36(8): 1958-1968.

Figures/Tables 7

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Table 1

Test function of CF1-CF6

Name	Definition	Global Minimum X*
CF1	$f (X) = ∑ i = 1 D x i 2$	$X * = (0, ⋯, 0)$
CF2	$f (X) = - 20 e x p - 0.2 1 / D ∑ i = 1 D x i 2 - e x p (1 / D ∑ i = 1 D c o s (2 π x i) + 20 + e x p (1)$	$X * = (0, ⋯, 0)$
CF3	$f (X) = ∑ i = 1 D - 1 [100 (x i + 1 - x i 2) 2 + (x i - 1) 2]$	$X * = (1, ⋯, 1)$
CF4	$f (X) = 10 D + ∑ i = 1 D [x i 2 - 10 × c o s (2 π x i)]$	$X * = (0, ⋯, 0)$
CF5	$f (X) = s i n 2 (π x i) + ∑ i = 1 D - 1 [(w i - 1) 2 (1 + 10 × s i n 2 (π w i + 1))] + (w d + 1) 2 [1 + s i n 2 (2 π w d)] w i = 1 + (x i - 1) / 4, i = 1, ⋯, d$	$X * = (1, ⋯, 1)$
CF6	$f (X) = ∑ i = 1 D (x i - 1) 2 - ∑ i = 2 D x i x i = 1$	$X i * = i (D + 1 - i), i = 1, ⋯, D$

Table 1

Table 2

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		CF1	CF2	CF3	CF4	CF5	CF6
最小值	CSO	1.554 6×10^-11	1.875 8	1.594 9×10^-5	1.831 7×10²	1.812 3×10²	4.286 4×10³
	SCSO	1.498 8×10^-28	1.373 3	6.113 5×10^-5	1.622 8×10²	1.850 3×10²	1.357 0×10⁴
	MCSO	1.182 7×10^-150	7.539 5×10^-15	1.600 5×10	1.780 9×10	9.323 3×10^-33	7.476 5×10²
	本文CSO	0	4.340 9×10^-16	1.817 7×10^-4	8.138 7×10	9.403 3×10^-33	3.137 3×10^-1
中间值	CSO	1.835 7×10^-99	4.137 9	2.278 7×10¹	4.118 1×10²	1.438 1×10³	5.053 9×10³
	SCSO	4.518 4×10^-27	3.437 5	1.961 1×10¹	4.337 2×10²	5.941 6×10³	1.467 0×10⁴
	MCSO	1.348 5×10^-14	1.475 5×10^-14	2.919 5×10¹	3.870 3×10¹	9.323 3×10^-33	7.057 9×10³
	本文CSO	0	1.501 5	2.081 6	1.323 2×10²	1.110 7×10	2.102 9×10³
均值	CSO	1.402 4×10^-91	5.336 4	5.639 8×10¹	4.971 0×10²	2.130 0×10³	5.264 9×10³
	SCSO	9.157 3×10^-21	4.524 1	4.037 0×10³	5.439 5×10²	6.304 3×10³	1.437 0×10⁴
	MCSO	2.588 3×10^-143	3.477 5	1.417 9×10²	4.121 5×10¹	2.101 4×10^-32	8.507 8×10³
	本文CSO	9.445 3×10^-105	1.687 5	5.631 4	1.417 1×10²	2.527 7×10¹	2.324 5×10³
标准差	CSO	1.028 5×10^-90	4.135 4	1.221 8×10²	2.710 3×10²	2.154 9×10³	8.475 2×10²
	SCSO	6.544 7×10^-20	4.128 0	2.858 5×10⁴	3.513 3×10²	4.316 4×10³	3.472 3×10^-2
	MCSO	1.548 7×10^-14	6.455 1	4.873 1×10²	1.778 8×10¹	2.431 0×10^-32	7.043 5×10³
	本文CSO	2.888 1×10^-10	7.690 8×10^-1	5.688 3	3.010 4×10¹	3.666 6×10¹	3.021 5×10³

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