A Fusion Method of Local Path Planning for Mobile Robots Based on LSTM Neural Network and Reinforcement Learning

Table 3

Data set.

No.	Input							Output
	dL	dLM	dM	dRM	dR	Angel_θ	rGR	ω
1	3.8487	5	3.3419	5	5	0	0	0.0441
2	3.6353	2.8085	2.8600	5	5	−0.0450	0.4806	−0.0734
3	3.4723	2.3934	2.6536	5	5	0.0289	0.4458	−0.0871
4	3.3491	2.0446	5	5	5	0.1181	0.4295	0.0124
5	3.2897	1.6592	5	5	5	0.1082	0.5362	0.0099
6	5	12964	5	5	5	0.1007	0.5525	0.0083
7	0.9444	0.9462	5	4.4307	4.4307	0.0947	0.5648	0.0072
8	0.6002	0.6010	5	4.0658	4.0658	0.0898	0.5743	0.0064
9	0.2599	5	5	3.7345	3.7345	0.0857	0.5815	0.0060
10	5	5	5	3.5361	3.5361	0.0820	0.5852	0.0055
52	5	5	5	3.0623	5	0.2163	1	0.0306