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CHAMP is an open-source ROS framework for configuring and controlling quadruped robots—not a single robot model you can buy. It includes locomotion control, robot-configuration tools, Gazebo simulation, and documented mapping and navigation examples. You can try those workflows without a physical robot; deploying them on hardware requires a compatible robot description, an actuator interface, and the sensors and drivers needed for navigation.
What CHAMP does—and what it does not
The CHAMP project describes a quadruped controller based on hierarchical control for dynamic locomotion. It supplies software and configuration workflows that can be adapted to different quadruped platforms. CHAMP computes joint angles; it does not, by itself, provide a complete robot with motors, sensors, wiring, or a universal hardware interface.
The control approach is linked to Jongwoo Lee’s MIT thesis, Hierarchical controller for highly dynamic locomotion utilizing pattern modulation and impedance control: implementation on the MIT Cheetah robot. MIT’s record identifies Lee as a scientist in mechanical engineering and dates the thesis to 2013. The thesis reports treadmill trot-running experiments with the MIT Cheetah reaching up to 6 m/s. That is a result for those experiments and that robot—not a CHAMP performance figure or a typical speed for a DIY quadruped. MIT thesis record
Try mapping and navigation in simulation
The documented examples use ROS with Gazebo and RViz. In the mapping workflow, the repository launches Gazebo, runs slam.launch with gmapping and move_base, and saves the resulting map. For autonomous navigation, it uses navigate.launch with AMCL and move_base; a destination is set in RViz using “2D Nav Goal.” These are the repository’s documented ROS workflows, not a ROS 2/Nav2 setup. CHAMP README and examples
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Simulation is useful for exploring the controller and navigation pipeline before connecting hardware, but a robot model must be prepared for the simulator. CHAMP’s README says a Gazebo-compatible URDF needs Gazebo compatibility and ros_control capability, including transmission definitions and suitable physical parameters such as mass, inertia, and foot friction. A model appearing in a configuration collection does not guarantee it will work unchanged in every simulator setup.
What a physical CHAMP build needs
For hardware deployment, CHAMP’s joint-angle output has to reach the robot’s actuators through an interface written or configured for that robot. The hardware guide describes a 12-DOF actuator output. It gives an interface pattern in which a hardware node subscribes to trajectory_msgs/JointTrajectory and publishes sensor_msgs/JointState on joint_states; builders can use ros_control or a custom ROS node. The base driver must already be running for the documented real-robot navigation workflow.
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Autonomous operation also needs an IMU publishing sensor_msgs/Imu on imu/data. The guide lists XV11, RPLidar, YDLIDAR X4, and SCIP 2.2-compliant Hokuyo lidar options. It explicitly says foot sensors are not required by the stock controller. These are integration pointers, not a guarantee that a particular sensor will work with every robot or setup. Check the sensor’s ROS driver and topic support, mounting and transforms, electrical requirements, and robot-specific calibration. CHAMP hardware integration guide, edited 2020-09-13
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The project describes two ways to run CHAMP with a physical robot. Neither establishes a universal required board; the right choice depends on the robot and its interface.
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| Path | What the project describes | What to verify |
|---|---|---|
| Linux machine | Run the ROS package on a Linux machine and connect a robot-specific hardware interface. | Confirm that the ROS environment, computer, drivers, and actuator interface match the intended build. |
| Teensy microcontroller | Use the project’s lightweight version on Teensy-series microcontrollers. | Confirm that the lightweight implementation supports the specific robot and required peripherals. |
The README lists Ubuntu 16.04 with ROS Kinetic and Ubuntu 18.04 with ROS Melodic as tested environments. Those are the project’s stated test environments, not a current recommendation or proof of compatibility with newer ROS releases. The hardware guide dates to 2020, so check the versions and dependencies against the exact build before relying on it. CHAMP README
Check the robot configuration before committing to a build
The companion CHAMP robot configuration repository contains configuration and URDF resources generated with the setup assistant and requires CHAMP to be installed. It identifies a Gazebo-compatible subset that includes ANYmal B, ANYmal C, Spot, Aliengo, Go1, A1, MIT Mini Cheetah, OpenDog V2, Open Quadruped, Stochlite, MangDang Mini Pupper, and Stanford Pupper. Treat that list as the repository’s stated support, not proof that every physical robot or sensor is plug-and-play; robot descriptions, dependencies, and simulator behavior can vary.
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- Confirm the exact robot has a suitable description and generated CHAMP configuration.
- For Gazebo, check the URDF’s simulator compatibility, transmissions, control support, and physical parameters.
- For hardware, identify how the joint trajectory reaches the actuators and how joint states are returned.
- For autonomous navigation, verify the IMU and lidar drivers, topics, mounting, transforms, and calibration for that robot.
Is CHAMP the right fit?
CHAMP is a useful starting point if you want to experiment with quadruped locomotion and ROS-based navigation, especially when simulation is an appropriate first step. It is not a shortcut around robot-specific engineering: physical use depends on an actuator interface, correct robot configuration, and—in an autonomous navigation setup—compatible sensors and drivers. The project documentation does not establish current ROS 2/Nav2 support or a universally recommended computer or actuator model.
If your question is “Do you only use RPi?”, the project documentation describes a Linux-machine route and a lightweight Teensy route, but does not specify a universal Raspberry Pi requirement. The Open Robotics discussion records that reader question; the project’s README is the more relevant source for its documented computing paths. Open Robotics project discussion, opened 2020-07-27
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