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index
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2.72M
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[ 0.6768927002588759, 0.13105158206783596, -0.13074507651991704, 1.3316205315663039, 1.2211894486955266, 0.5280358770139266 ]
[ -0.13065512478351593, 0.8907014727592468, -0.9073050618171692, -0.6595202684402466, -0.3250052034854889, 0.21605069935321808 ]
torque
-0.295441
false
false
halfcheetah
other
flat
simulation
99
0
99
1.98
[ 0.014644453857932836, 0.06931784695883234, -0.30176665862485036, 0.05966719722500312, -0.2818398015884386, -0.24375096730785567 ]
[ 0.14795591498699648, 0.16608756466445798, 0.022429940918736103, -0.11590559034995751, -0.1485569564033787, -0.40930968356570785 ]
[ -0.5231114625930786, -0.4464518129825592, -0.1036849245429039, -0.7030388712882996, 0.5458899736404419, -0.6665104031562805 ]
torque
-0.117351
false
false
halfcheetah
other
flat
simulation
End of preview. Expand in Data Studio

Open Locomotion Skills Dataset (OLSD) v0.1

A unified benchmark dataset for legged robot locomotion across diverse morphologies.

Dataset Description

OLSD provides expert, random, and domain-randomized trajectories for training and evaluating locomotion policies. All data is collected from MuJoCo/Gymnasium environments.

Metric Value
Total Episodes ~4,200
Total Steps ~2,722,712
Robots HalfCheetah, Ant, Walker2d, Hopper
Quality Tiers random, expert, domain_random
Format Parquet + metadata JSON

Benchmark Results

Robot Algorithm Norm. Score Return
Hopper PPO 108.4 3,507.9
Walker2d SAC 107.3 4,928.5
Ant PPO 29.7 1,733.2
HalfCheetah PPO 18.0 1,955.4

Usage

from datasets import load_dataset

# Load the full dataset
ds = load_dataset("kanishqgandharv/olsd-v0.1")

# Or load a specific robot
ds = load_dataset("kanishqgandharv/olsd-v0.1", data_files="halfcheetah/**/*.parquet")

Or with the OLSD SDK:

import olsd
dataset = olsd.load("./data/olsd-v0.1-final")
print(dataset.summary())

Data Schema

Each row contains:

  • observation.joint_positions -- Joint angles (rad)
  • observation.joint_velocities -- Joint velocities (rad/s)
  • action -- Motor commands
  • reward -- Reward signal
  • done -- Terminal flag

Links

License

Apache 2.0

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