A Smooth Jump Point Search Algorithm for Mobile Robots Path Planning Based on a Two-Dimensional Grid Model

Table 1

Three sets of static map simulation data.

Map	Algorithm	Path length/m	Path length optimization ratio	Number of turning points	Turning point optimization ratio	Number of extended nodes/number	Path safety	Algorithm search time/ms	Path convergence or not
1	Traditional ACO	43.9411	—	5	—	—	N	107.87	Y
	Improved ACO [26]	47.4558	—	2	—	—	Y	98.71	Y
	Traditional A	43.9411	—	5	—	346	N	9.47	—
	Safety A	45.6985	—	11	—	370	Y	9.18	—
	Improved A [25]	43.10	4.9%	0	100%	40	Y	6.82	—
	PRM	43.3658	—	4	—	—	Y	15.44	—
	This paper	42.4743	7.0%	0	100%	52	Y	6.20	—
2	Traditional ACO	77.6396	—	18	—	—	N	266.32	N
	Improved ACO [26]	76.4392	—	6	—	—	Y	180.54	Y
	Traditional A	72.2254	—	7	—	504	N	13.48	—
	Safety A	76.9117	—	13	—	772	Y	19.96	—
	Improved A [25]	71.69	5.7%	0	100%	64	Y	8.700	—
	PRM	72.1034	—	4	—	—	Y	25.67	—
	This paper	71.3966	7.1%	0	100%	47	Y	8.37	—
3	Traditional ACO	352.374	—	>30	—	—	N	458.62	N
	Improved ACO [26]	173.9828	—	5	—	—	Y	82.6	Y
	Traditional A	148.2048	—	9	—	2527	N	85.82	—
	Safety A	151.7229	—	9	—	2750	Y	85.70	—
	Improved A [25]	143.35	5.5%	0	100%	120	Y	15.50	—
	PRM	148.4120	—	3	—	—	Y	35.27	—
	This paper	143.0791	6.0%	0	100%	22	Y	14.29	—