Crushing of blasted ore is an essential phase in extraction of valuable minerals in mining industry. It is typically performed in multiple stages with each stage producing finer fragmentation. Performance and throughput of the first stage of crushing is highly dependent on the size distribution of the blasted ore. In the crushing plant, a metal grate prevents oversized boulders from getting into the crusher jaws, and a human-controlled hydraulic manipulator equipped with a rock hammer is required to break oversized boulders and ensure continuous material flow. This secondary breaking task is event-based in the sense that ore trucks deliver boulders at irregular intervals, thus requiring constant human supervision to ensure continuous material flow and prevent blockages. To automatize such breaking tasks, an intelligent robotic control system along with a visual perception system (VPS) is essential. In this manuscript, we propose an autonomous breaker system that includes a VPS capable of detecting multiple irregularly shaped rocks, a robotic control system featuring a decision-making mechanism for determining the breaking order when dealing with multiple rocks, and a comprehensive manipulator control system. We present a proof of concept for an autonomous robotic boulder breaking system, which consists of a stereo-camera-based VPS and an industrial rock-breaking manipulator robotized with our retrofitted system design. The experiments in this study were conducted in a real-world setup, and the results were evaluated based on the success rates of breaking. The experiments yielded an average success rate of 34% and a break pace of 3.3 attempts per minute.

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In this paper, a nonlinear model-based controller with parameter identification is designed for a rigid open-chain manipulator arm actuated by servovalve-controlled hydraulic cylinders. The arising problem in adopting model-based controllers is how to acquire accurate estimates of system parameters, with limited available information about either the hydraulic actuator parameters or manipulator link inertial parameters. The objective of this study is to identify both the rigid-body parameters of the links and the hydraulic actuator parameters from collected cylinder chamber pressure and joint angle data, while no a priori knowledge of these parameters is available. Same physical plant models are used for control design as well as for parameter identification. Experimental results show that the proposed nonlinear model-based control scheme results in acceptable Cartesian position tracking performance in free-space motion when using the identified parameters.

Wheeled mobile platforms are important subsystems of heavy-duty working machines, but precise motion control of vehicles with multiple actuated wheels can be challenging, as linear controllers relying solely on velocity feedback could lead to excessive slippage of the wheels in face of varying terrain conditions. When aiming for more advanced control tasks as opposed to path-following, torque control of individual wheels could become necessary in order to distribute the traction effort in a desired fashion between each wheel. Studies on dynamic-model-based control of wheeled mobile robots concentrate on eletrically driven platforms that exhibit more linear behaviour than hydraulic drives, and dynamics of hydraulic motors are rarely addressed in the control design. In this paper, a model-based control design is pursued for a four-wheel vehicle actuated by in-wheel hydraulic motors, all independently controllable by high-bandwidth valves. Experiments on a heavy-duty mobile platform, equipped with wheel odometry, pressure transducers and satellite positioning, are conducted to study the feasibility of the proposed controller.