LabDex: A Hierarchical Benchmark for Dexterous Manipulation in Laboratories

Zhipeng Tang; Sihang Chen; Sha Zhang; Peihao Yang; Yan Liu; Wentao Zhao; Xinrui Liu; Rui Huang

cs.ROAug 19, 2026

LabDex: A Hierarchical Benchmark for Dexterous Manipulation in Laboratories

Authors: Zhipeng Tang, Sihang Chen, Sha Zhang, Peihao Yang, Yan Liu, Wentao Zhao, Xinrui Liu, Rui Huang, +6 more

Organizations: University of Science and Technology of China · The Chinese University of Hong Kong · iFLYTEK

Abstract

Autonomous laboratories hold great promise for accelerating scientific discovery. To achieve this vision, robots are supposed to dexterously manipulate diverse labware and instruments and execute long-horizon, state-dependent experimental procedures. Yet existing benchmarks do not jointly capture dexterous hand use, real-world laboratory interactions, and multi-stage experimental procedures, limiting systematic training and evaluation. To bridge this gap, we introduce LabDex, a large-scale real-world dataset and benchmark for dexterous manipulation in chemistry laboratories, organized around a hierarchical task taxonomy spanning atomic skills, compositional tasks, and long-horizon experiments. First, LabDex is cross-platform and, for the first time, unifies real-world and simulation platforms under a common framework, providing standardized task definitions, demonstrations, and evaluation protocols. Second, LabDex is large-scale and systematically organizes chemistry laboratory operations into three interconnected levels: Atomic Skills, which characterize fundamental dexterous manipulation capabilities; Compositional Skills; and Long-Horizon Laboratory Workflows. This hierarchical design not only supports the evaluation of end-task performance, but also enables the analysis of how fundamental dexterous skills compose and influence more complex laboratory operations. We conduct cross-level evaluations of representative robot learning methods in both real-world and simulation environments. The experimental results validate the effectiveness of the LabDex task design and demonstration data, and show that the benchmark supports the training and systematic evaluation of existing robotic policies across laboratory dexterous manipulation tasks at different levels, providing a foundation for further research and development of autonomous laboratory robots.

Figures & tables

Dataset / Benchmark	Laboratory Domain	Dexterous Hand	Simulation	Real Robot	Task Diversity
					Atomic	Compositional	Long-horizon
Bi-DexHands ( Chen et al. 2022 )	✗	✓	✓	✗	✓	✓	✗
DexArt ( Bao et al. 2023 )	✗	✓	✓	✗	✓	✗	✗
DexCap ( Wang et al. 2024 )	✗	✓	✗	✓	✓	✓	✗
DexVerse ( Yao et al. 2026 )	✗	✓	✓	✗	✓	✓	✓
Chemistry3D ( Li et al. 2024 )	✓	✗	✓	✗	✓	✓	✗

Table 1: Comparison with existing datasets and benchmarks.

Figure 1: Overview of LabDex. LabDex is a hierarchical benchmark built on unified real-world and simulation platforms. It contains three task levels: Atomic Skills , Compositional Skills , and Long-Horizon Laboratory Workflows . The dataset is collected using a Franka Research 3 robot arm equipped with an XHand dexterous hand and covers a diverse set of laboratory objects.

Figure 2: Real-world and simulation data collection pipeline.

Skill Type	DP	ACT	${\pi}_{0.5}$
Pick	$0.05$	$0.25$	$\mathbf{0.46}$
Place	$0.01$	$0.64$	$\mathbf{0.92}$
Insert	$0.00$	$0.25$	$\mathbf{0.30}$
Pour	$0.00$	$0.23$	$\mathbf{0.66}$
Press	$0.00$	$0.00$	$\mathbf{0.12}$
Shake	$0.00$	$\mathbf{0.90}$	$0.88$

Table 2: Average performance of atomic skill categories. We evaluate a total of 26 atomic skill instances, with each task evaluated over 50 trials for every model. Complete results for all atomic skills are provided in Appendix B.

Task	Sub-task	DP	ACT	${\pi}_{0.5}$
pour_the_water_from the_right_beaker_into the_left_one	pick_up_the_beaker_on_the_right	$0.00$	$0.70$	$0.62$
	pour_the_water_from_the_handheld_beaker_into_the_one_on_the_table	$0.00$	$0.48$	$0.32$
	place_the_beaker_back_on_the_table	$0.00$	$0.48$	$0.00$
	Avg. Len.	$0.00$	$\mathbf{1.66}$	$0.94$
put_the_100ml_beaker on_the_electronic balance	pick_up_the_100ml_beaker	$0.00$	$0.12$	$0.72$
	put_the_100ml_beaker_on_the_electronic_balance	$0.00$	$0.12$	$0.70$

Table 3: Performance of compositional skills. Each task is evaluated over 50 trials for every model.

Task	Sub-task	DP	ACT	${\pi}_{0.5}$
add_the_NaCl_from the_weighing_funnel to_the_round_bottom flask	pick_up_the_funnel_from_the_transparent_funnel_stand	$0.00$	$0.40$	$0.54$
	place_the_funnel_on_the_round_bottom_flask	$0.00$	$0.00$	$0.02$
	pick_up_the_weighing_funnel	$0.00$	$0.00$	$0.02$
	pour_all_the_NaCl_from_the_weighing_funnel_into_the_round_bottom_flask	$0.00$	$0.00$	$0.02$
	put_the_weighing_funnel_back_on_the_table	$0.00$	$0.00$	$0.02$
	remove_the_funnel_from_the_round_bottom_flask	$0.00$	$0.00$	$0.00$

Table 4: Performance of long-horizon laboratory workflows. Each task is evaluated over 50 trials for every model.

Task	Sub-task	DP	ACT	${\pi}_{0.5}$
put_the_200ml_beaker on_the_electronic balance	pick_up_the_200ml_beaker	$0.00$	$0.26$	$0.58$
	put_the_200ml_beaker_on_the_electronic_balance	$0.00$	$0.24$	$0.54$
	Avg. Len.	$0.00$	$0.46$	$\mathbf{1.12}$
pour_the_water_from the_graduated_cylinder into_the_round_bottom flask	pick_up_the_graduated_cylinder	$0.00$	$0.00$	$0.00$
	pour_the_water_from_the_graduated_cylinder_into_the_round_bottom_flask	$0.00$	$0.00$	$0.00$
	put_the_graduated_cylinder_back_on_the_table	$0.00$	$0.00$	$0.00$

Table 5: Performance of compositional skills in simulation. Each task is evaluated over 50 trials for every model.

Table 8

Appendix figures & tables3 assets

Supplementary material from the paper’s appendix.

Appendix

Type	Task	DP	ACT	${\pi}_{0.5}$
Pick	pick_up_the_round_bottom_flask	$0.00$	$0.02$	$0.12$
	pick_up_the_beaker_on_the_right	$0.38$	$0.38$	$0.86$
	pick_up_the_100ml_beaker	$0.00$	$0.02$	$0.82$
	pick_up_the_200ml_beaker	$0.06$	$0.36$	$1.00$
	pick_up_the_test_tube	$0.00$	$0.08$	$0.06$
	take_the_glass_rod_from_the_white_test_tube_rack	$0.02$	$0.24$	$0.22$

Appendix

Table 9: Performance of atomic skills. Each task is evaluated over 50 trials for every model.

Task	DP	ACT	${\pi}_{0.5}$
pick_up_the_round_bottom_flask	$0.00$	$0.00$	$0.56$
pick_up_the_beaker	$0.34$	$0.22$	$0.64$
put_the_beaker_on_the_electronic_balance	$0.08$	$0.32$	$0.02$
pick_up_the_graduated_cylinder	$0.00$	$0.04$	$0.26$
pour_the_water_from_the_graduated_cylinder_into_the_round_bottom_flask	$0.52$	$0.74$	$0.72$
put_the_graduated_cylinder_back_on_the_table	$0.00$	$0.08$	$0.92$

Appendix

Table 10: Performance of atomic skills in simulation. Each task evaluated over 50 trials for every model.

Panel of Figure 3 — Figure 3: Examples of selected atomic skills.

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