Dynamic Robot Locomotion and Motion

Course dates – HT – week beginning Monday 11th February 2019 – for Year 1 students
Maurice Fallon and Ioannis Havoutis


The vast majority of the world is inaccessible to today’s robots. For a robot to explore a forest or disaster situation or enter our homes, it will need to be dynamically balancing and standing on legs. Locomotion brings an array of perception and navigation challenges which make it difficult to understand a robot’s environment and to achieve robust reactive control. This course will to introduce you to walking robotics using state of the art simulation and software tools.

  • To understand the basic principles of locomoting robots. To understand the state of the art of the field.
  • To learn about locomotion gaits, torque control, localization and planning.
  • To gain experience in debugging, system design, team work and communication.
  • To understand the underpinning technology of state estimation, lidar sensing and obstacle detection
  • Ability to program in C++
  • CDT-gleaned knowledge on computer vision and estimation
Lecture Notes

Each day will being with a series of introductory lectures of (1) walking robotics (2) control (3) ROS (Robot Operating System) and its tools (4) path planning. There will also be a daily research lecture. The practical will be supported by members of the Dynamic Robotics Systems Group to help with problem solving and debugging.

Other Sources

The Dynamic Robot Systems Group will provide you with a fully prepared system running the latest version of ROS and the Gazebo simulation of the Anymal robot from Anybotics. This will come with key software from ROS for control of the robot and sensor visualisation.


The course will be built around a single extensive practical. You will be split into teams and at the end of the week you will compete against each other in a pathfollowing course by programming the simulated Anymal to detect obstacles, walk around them and plan to the goal.

Assessment Mode

You will give a presentation of your results and critique of your system on the last day of the challenge. Each day students will present their progress. There will be a final competition in which each team will demonstrate their approach in the Gazebo simulator.