Mika Hyvönen

Modeling and motion control of an articulated-frame-steering hydraulic mobile machine

The paper addresses autonomous motion control (path-following in particular) of an articulated-frame-steering (AFS) hydraulically actuated mobile machine. We first propose a kinematic model of the vehicle, together with a simple model for steering hydraulic actuator. The kinematic model is derived under simplifying assumptions that there are no slipping and no skidding. The accuracy of the model is then validated using an elaborated semi-empirical hardware-in-the-loop simulator (GIMsim) of an AFS machine built at IHA/TUT. A motion control strategy is then proposed and a path-following control law is derived. Finally, the efficacy of the methodology is shown using GIMsim.

Position-based visual servoing for pallet picking by an articulated-frame-steering hydraulic mobile machine

This paper addresses a visual servoing problem for a mobile manipulator. Specifically, it investigates pallet picking by using visual feedback using afork lift truck. A manipulator with limited degrees of freedom and differential constraint mobility together with large dimensions of the machine require reliable visual feedback (pallet pose) from relatively large distances. To address this challenge, we propose a control architecture composed of three main sub-systems: (1) pose estimation: body and fork pose estimation in the pallet frame; (2) path planning: from the current pose to the origin (pallet frame); and (3) feedback motion control. In this architecture, the pallet becomes the local earth fixed frame in which poses are resolved and plans are formulated. Choosing the pallet as the origin provides a natural framework for fusing the wheel odometry/inertial sensor data with vision, and planning is required only once the pallet is detected for the first time (because the target is always the origin). Visual pallet detection is non-real-time and unreliable, especially owing to large distances, unfavorable vibrations, and fast steering. To address these issues, we introduce a simple and efficient method that integrates the vision output with odometry and realizes smooth and non-stop transition from global navigation to visual servoing. Real-world implementation on a small-sized forklift truck demonstrates the efficacy of the proposed visual servoing architecture.

A Survey of Analysis, Modeling, and Diagnostics of Diesel Fuel Injection Systems

Diesel engines are widely used due to their high reliability, high thermal efficiency, fuel availability, and low consumption. They are used to generate power, e.g., in passenger cars, ships, power plants, marine offshore platforms, and mining and construction machines. The engine is at heart of these applications, so keeping it in good working condition is vital. Recent technical and computational advances and environmental legislation have stimulated the development of more efficient and robust techniques for the diagnostics of diesel engines. The emphasis is on the diagnostics of faults under development and the causes of engine failure or reduced efficiency. Diesel engine fuel injection plays an important role in the development of the combustion in the engine cylinder. Arguably, the most influential component of the diesel engine is the fuel injection equipment; even minor faults can cause a major loss of efficiency of the combustion and an increase in engine emissions and noise. With increased sophistication (e.g., higher injection pressures) being required to meet continuously improving noise, exhaust smoke, and gaseous emission regulations, fuel injection equipment is becoming even more susceptible to failure. The injection systems have been shown to be the largest contributing factor in diesel engine failures. Extracting the health information of components in the fuel injection system is a very demanding task. Besides the very time-consuming nature of experimental investigations, direct measurements are also limited to selected observation points. Diesel engine faults normally do not occur in a short timeframe. The modeling of typical engine faults, particularly combustion related faults, in a controlled manner is thus vital for the development of diesel engine diagnostics and fault detection. Simulation models based on physical grounds can enlarge the number of studied variables and also obtain a better understanding of localized phenomena that affect the overall behavior of the system. This paper presents a survey of the analysis, modeling, and diagnostics of diesel fuel injection systems. Typical diesel fuel injection systems and their common faults are presented. The most relevant state of the art research articles on analysis and modeling of fluid injection systems as well as diagnostics techniques and measured signals describing the behavior of the system are reviewed and the results and findings are discussed. The increasing demand and effect of legislation related to diagnostics, especially on-board diagnostics (OBD), are discussed with reference to the future progress of this field.

A mapping method tolerant to calibration and localization errors based on tilting 2D laser scanner

Autonomous mobile machines use onboard sensors for navigation and obstacle avoidance. The accuracy of the sensor data in global frame is however dependent on the localization accuracy of the machine. Simultaneous localization and mapping algorithms (SLAM) are widely used with 3D laser scanners for mapping the world. They use scan matching algorithms to solve the accuracy problem by matching prior sensor data of the environment with the newly acquired data. However matching scans is not always possible. Insufficient amount of prior data or too few features in the scan can prevent the scan matching algorithm from finding a match. Thus it is important that also the mapping algorithm is tolerant to some degree of error in localization and calibration. We present a method for generating obstacle maps from smaller data segments at a time, thus making the mapping system more tolerant to navigation and calibration errors. The obstacle mapping method is tested with modified Avant multipurpose loader.

Fuel Optimal Controller for Hydrostatic Drives: A Simulation Study and Model Validation

This paper presents an optimal controller for fuel efficiency of a hydraulic mobile machine with hydrostatic drive (HSD). The solution is validated using a semi-empirical simulated research platform. The drive transmission of the machine includes one variable displacement hydraulic pump and four two-speed hub motors. There is no energy storage installed. Thus, the structure of the HSD and presented improvements in fuel economy are comparable to traditional machines.The optimal controller is compared to a baseline controller that intuitively keeps the components at their high efficiency regions. In simulated hill tests, fuel economy was improved by up to 25.9 % depending on the slope of the hill and velocity reference.Copyright

Assistive Situation Awareness System for Mobile Multimachine Work Environments

Mobile multimachine work environments, in general, consist of varying types of machines driving across a site to complete a moving or manipulation task. As the view from the machines over the environment can be limited due to the structure of the machines, the environment, and the moved/manipulated items, there is a risk of collision between machines. In this paper, we propose a situation awareness system aimed as a driver/operator assistive system to enhance the safety and efficiency of multimachine work environments. The system consists of the pose estimation of the machines, the M2M communication based on IEEE 802.11p, the future pose prediction of the machines, and a graphical user interface. The system is designed to be general enough to be applicable in diverse work environments, which is most easily implemented as a retrofit for existing machines. In this paper, the implementation of the system presented is a proof of concept, and the focus is on how the overall system works in a real harbor environment during operation, ultimately aiming for the collision avoidance of harbor machines. The field tests show promising results, particularly regarding the applicability of the M2M communication technology in a very challenging and uncertain harbor environment.