srb agent teleop — Teleoperate Agent

The srb agent teleop command allows you to manually control robots in the environment using various input devices. This is useful for testing the environment and observing the behavior of the agent under specific control inputs.

Usage

srb agent teleop --env ENV_ID [options]

Options | Shared Agent Options

Teleoperation Modes

The teleop subcommand supports 2 modes of operation based on the environment action space:

• Direct Teleoperation
• Teleoperation via Policy

Direct Teleoperation

Direct teleoperation is available for environments with action spaces that can be mapped into high-level control commands, such as the desired end-effector pose or acceleration of a mobile robot.

Examples

Teleoperate a robot in the _manipulation template environment:

• Use the ur10 manipulator

srb agent teleop -e _manipulation env.robot=ur10

Teleoperate a robot in the _orbital template environment:

• Use the spacemouse input teleoperation device

srb agent teleop -e _orbital --teleop_device spacemouse

Teleoperation via Policy

Some action spaces do not support direct teleoperation due to their complexity or dimensionality, such as joint-space control of a humanoid robot. In such cases, you can still teleoperate the agent by providing a trained policy (only RL agents are currently supported). In this case, command-like observations are driven by the teleoperation device, and the policy generates the corresponding actions.

Examples

Reference: Reinforcement Learning Workflow
Reference: srb agent train — Train Agent

First, you need to train an RL agent using the srb agent train command. Let's demonstrate this with the locomotion_velocity_tracking environment using the dreamer algorithm:

srb agent train --headless --algo dreamer -e locomotion_velocity_tracking env.num_envs=256

After you have successfully trained a policy, you can teleoperate the agent:

srb agent teleop --algo dreamer -e locomotion_velocity_tracking

By default, the policy will be loaded from the latest checkpoint. However, you can specify a specific checkpoint using the --model option.

srb agent teleop --algo dreamer -e locomotion_velocity_tracking --model space_robotics_bench/logs/locomotion_velocity_tracking/dreamer/...