tabletask 0.2.3

tabletask

A minimal, object-centric format to author tabletop manipulation tasks in simulation, from simple to complex.

A task says where things start and what must become true:

{
  "id": "robolab-banana_in_bowl",
  "instruction": "Pick up the banana and place it in the bowl.",
  "start": [
    ["on", "banana", "table"],
    ["on", "bowl", "table"]
  ],
  "goal": [
    ["inside", "banana", "bowl"]
  ]
}

Objects carry named regions that tasks place things in and check against.

Installation

pip install tabletask
pip install "tabletask[control]"
pip install "tabletask[rtx]"

Example

import tabletask

env = tabletask.make("robolab-banana_in_bowl")
obs, info = env.reset(seed=0)

for _ in range(600):
    action = [*obs["robot"]["joint_position"], 0.0]
    obs, reward, terminated, truncated, info = env.step(action)
    if terminated or truncated:
        break

print("success:", info["success"])
env.close()

Several environments at once, each in its own process and renderer:

envs = tabletask.make("robolab-banana_in_bowl", num_envs=8, gpus=[0])
observations, infos = envs.reset(episodes=range(8))
observations, rewards, terminated, truncated, infos = envs.step(actions)
envs.close()

Acknowledgments

Tasks are ported from ABC and RoboLab. The robot models come from MuJoCo Menagerie.