Semi-Autonomous Bulldozer Blade Control Using Real-Time Terrain Mapping

This paper considers semi-autonomous excavation done by heavy-duty bulldozers with an onboard front-mounted blade. The goal is to gradually manipulate the blade digging depth to maximize the amount of excavated soil while considering the approaching terrain shape, traction, and the mobile base inclination. With the proposed system, the operator provides the target load on the machine and the blade is controlled semi- autonomously, while the operator can focus on driving the mobile base. To reduce large load variations caused by terrain shape irregularities affecting the blade, our system uses an onboard lidar to generate an elevation map of the terrain, updating it online as the machine moves. From the discrete map, we generate a well- behaved function describing the terrain shape. This provides a nominal blade elevation path that is modified online based on the measured load on the machine to maneuver the blade gradually, avoiding large gradient changes. The resulting Cartesian elevation profile is used as a reference to a blade position controller that counteracts the mobile base inclination. A commercial bulldozer with no modifications to its original hydraulics was used as an experimental platform, and the results verify the efficacy of the proposed methods in challenging outdoor conditions.