Task Environments

Task Environments#

Task environments combine a simulation scene, robot, and task logic behind a Gymnasium-compatible interface. Official classic-control, locomotion, manipulation, and special tasks are included in the main embodichain installation through the embodichain_tasks package.

Find a Task#

embodichain list-task
embodichain list-task --category manipulation
embodichain show-task embodichain_tasks:repeated_pick_place

See Supported Tasks for supported tasks and their configuration paths. Preview a task with its runnable JSON or YAML configuration:

embodichain run-task \
    --gym_config embodichain_tasks/configs/tasks/manipulation/repeated_pick_place/task.ur5.yaml \
    --preview

See Running Tasks with run-task for rollout, recording, and replay options, or Reinforcement Learning Training to train an RL policy.

Create a Task#

Start from the task template. Use an EmbodiedEnv subclass for custom Python behavior, or compose a configuration-defined Task Program from reusable components. Third-party task packages are discovered through the embodichain.tasks entry point. See Embodied Environments for environment authoring and Configure and Run an Embodied Task Program for Task Programs. The official task package README describes package layout and registration.

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