Robot Navigation on BARN 300 Environments (test) benchmark leaderboard · SOTA2 Research

Robot Navigation on BARN 300 Environments (test)

94.34Success RateAPPLV-RLFT

Evaluation Results

Method	Links
APPLV-RLFT2026.03		94.34	13.63	0.463	1.98	3.68
APPLV-SL2026.03		92.68	15.28	0.44	1.66	5.65
Zero-Shot VLM2026.03		92.5	16.18	0.417	0.5	4
APPLV-RLFT2026.03		90.3	12.51	0.441	8.9	0.7
Transformer BC2026.03		90.25	20.35	0.383	2.1	7.64
APPLV-SL2026.03		90	17.61	0.429	0.78	9.22
APPLV-RLFT2026.03		89.7	16.75	0.434	7.3	3
Heuristic Expert2026.03		89.5	16.09	0.418	2.38	8.12
Zero-Shot VLM2026.03		89.31	16.64	0.398	1.07	9.61
APPLV-SL2026.03		88.93	17.82	0.415	9.84	1.22
APPLV-RLFT2026.03		87.2	18.68	0.374	6.51	6.29
Heuristic Expert2026.03		86.61	19.11	0.388	0.58	12.81
APPLV-SL2026.03		86.1	21.58	0.357	7.51	6.39
Transformer BC2026.03		85.57	18.16	0.411	2.36	12.05
APPLR2026.03		85.35	15.66	0.404	7.93	6.72
Zero-Shot VLM2026.03		85.24	22.02	0.367	8.02	6.74
Heuristic Expert2026.03		84.48	23.41	0.365	14.17	1.35
Transformer BC2026.03		83.68	20.42	0.378	6.52	9.8
Transformer BC2026.03		83.03	27.58	0.323	8.21	8.75
Heuristic Expert2026.03		82.47	25.83	0.328	7.5	10.03
Zero-Shot VLM2026.03		81	31.27	0.301	10	9
APPLR2026.03		79.17	20.29	0.362	5.53	15.3
APPLR2026.03		78.53	24.73	0.356	7.4	14.07
APPLR2026.03		73.15	27.38	0.296	11.87	14.98