Central to MEMMO and the research projects of the Dynamic Robotic Systems (DRS) group of the Oxford Robotics Institute (ORI) is the translation of research results into industry-led use cases. More generally, the transfer of robotics and AI knowledge into industry is one of the key aims of MEMMO. As part of this agenda, ORI held an initial field trial at the Fire Service College in Gloucestershire to test the capability of the platform for MEMMO field trials.

The site hosts a number of test sites, usually used to train fire fighters, but for this event it was taken over by robots to see if our technology was able to perform a range of tasks far away from controlled lab conditions. As appropriate for research targeting industrial facilities, our demonstrations took place on an oil rig mock-up, complete with fire damaged living compartments, a variety of storage vessels, and treacherous surfaces. The event was attended by representatives from the construction and oil & gas industries.

Figure 1: Overview of the Oil Rig facility at the Fire Service College.

The ORI demonstrations focused on showcasing our research around autonomous systems for industrial inspection and monitoring. For this we are developing technology to provide robust autonomous navigation and localisation across a variety of extreme environments, and perceptual capabilities for long-term structural monitoring and change detection.

Figure 2: The ANYmal robot walking through the oil rig facility.

In this first trial, we showcased DRS’s research on legged mobility for inspection. This was done using the ANYmal quadruped robot and DRS’s home-developed remote operation software stack, that allows the operator to supervise the progress of the mission and plan the robot’s next actions. The robot started at a distance to the oil rig and demonstrated its ability to localise its position relative to a prior 3D model of the environment using LIDAR.

Figure 3: Examples of successfully and drifting localization.

Figure 4: Localisation with respect to a prior map using the LIDAR.

After this, ANYmal was asked to reach a target area within the oil rig. First, it navigated through the main corridor and over patches of uneven tarmac. Then, the robot needed to overcome a 25cm separating barrier. We took advantage of ANYmal’s very large range of motion to invert its leg configuration and to traverse the barrier. The quadruped then navigated to an industrial staircase, using a speedy trotting gait and climbed the steps up using a walking gait called FreeGait. Once it reached the landing it entered the facility and explored the connected rooms.

Figure 5: The ANYmal inspecting a set of connected rooms in poor lighting conditions.

The event also featured further ANYmal demonstrations from University of Edinburgh, another MEMMO partner. Haptic compliant locomotion was tested and data was collected for footstep planning projects within the MEMMO project.

You can watch a video of this trial here: