Towards Semi-Autonomous Control of Heavy-Duty Tracked Earth-Moving Mobile Manipulators : Use Case: The Bulldozer

A mobile manipulator (MM) comprises a manipulator attached to a mobile base, making it capable of manipulation tasks in large workspaces. In the field of construction, heavy-duty MMs are extensively used for soil excavation at construction sites. One such machine is the bulldozer, which is widely used because of its robustness and maneuverability. With its onboard blade, the bulldozer shapes terrain and transports soil material by pushing it. However, operating the blade with joysticks to accurately shape the terrain surface and moving material productively are difficult tasks that require extensive training and experience. Automating the motion of the blade, therefore, has the potential to reduce skill requirements, improve productivity, and reduce operators’ workloads. This thesis studies and develops methods for the semi-autonomous control of a bulldozer to increase surface quality and earthmoving productivity. These goals were reflected in the main research problems (RPs). Furthermore, as bulldozers drive over the terrain shape generated by the blade, the RPs are coupled because earthmoving productivity is partially dependent on surface quality. The RPs and their coupling were addressed in four publications by coordinating the mobile base and manipulator control and by using the surrounding terrain shape in automatic blade motion reference computations. Challenges to automatic control emerge from the tracked mobile platform driving on rough terrain while the manipulator tool interacts with the soil. It is shown in the first two publications that coordinating the control of the MM mobile base and blade manipulator subsystems can improve surface quality and productivity by temporarily slowing down the machine when the required manipulator joint rates increase or when the tractive performance reduces. The third publication showed that feedforward–feedback control of the blade manipulator can be used on a real-world bulldozer for accurate terrain shaping. The thesis work culminates in the final publication with an experimental implementation of a semi-autonomous blade control system that continuously maps the worksite terrain and uses it to compute the required blade motion