For human-robot cooperative spray painting robot, offline programming based on predefined model of the unpainted object is a robust and efficient method for trajectory generation. To apply the programmed trajectory on...
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ISBN:
(数字)9781728107707
ISBN:
(纸本)9781728107714
For human-robot cooperative spray painting robot, offline programming based on predefined model of the unpainted object is a robust and efficient method for trajectory generation. To apply the programmed trajectory on the unpainted object, the relative pose between the object and the predefined model needs to be acquired. Nevertheless, acquiring an accurate estimation of the pose in spray painting setting remains a problem. To address this, a RGB-D pose estimation system based on deep learning and iterative closest point (ICP) alignment is proposed in this paper. The perception module of this system is RGB-D sensor. The RGB-D image of the object is segmented using Fully Convolutional Network (FCN) with RGB-D input. The resulting segmented point cloud is aligned with the model candidates using ICP algorithm to estimate the pose of the object. It is validated in the experiments that the proposed system and methods are effective and robust.
The procedures for the engineering, synthesis, simulation and targeted implementation of algorithms for solving optimization problems in hierarchical automated controlsystems require complex objects using a variety o...
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The procedures for the engineering, synthesis, simulation and targeted implementation of algorithms for solving optimization problems in hierarchical automated controlsystems require complex objects using a variety of mathematical and software and hardware for research and engineering work. In this article the unification of mathematical and algorithmic support in the form of a unified concept of solving optimal control is proposed. We propose to use LabVIEW software and CompactRIO industrial controller as the unification of software and hardware implementation of mathematical-algorithmic developments, on which developed software tools to solve optimization problems using genetic algorithm.
Human joint dynamic stiffness plays an important role in the stability of performance augmentation exoskeletons. In this paper, we consider a new frequency domain model of the human joint dynamics which features a com...
Human joint dynamic stiffness plays an important role in the stability of performance augmentation exoskeletons. In this paper, we consider a new frequency domain model of the human joint dynamics which features a complex value stiffness. This complex stiffness consists of a real stiffness and a hysteretic damping. We use it to explain the dynamic behaviors of the human connected to the exoskeleton, in particular the observed non-zero low frequency phase shift and the near constant damping ratio of the resonance as stiffness and inertia vary. We validate this concept with an elbow-joint exoskeleton testbed (attached to a subject) by experimentally varying joint stiffness behavior, exoskeleton inertia, and the strength augmentation gain. We compare three different models of elbow-joint dynamic stiffness: a model with real stiffness, viscous damping and inertia; a model with complex stiffness and inertia; and a model combining the previous two models. Our results show that the hysteretic damping term improves modeling accuracy (via a statistical F-test). Moreover, this term contributes more to model accuracy than the viscous damping term. In addition, we experimentally observe a linear relationship between the hysteretic damping and the real part of the stiffness which allows us to simplify the complex stiffness model down to a 1-parameter system. Ultimately, we design a fractional order controller to demonstrate how human hysteretic damping behavior can be exploited to improve strength amplification performance while maintaining stability.
In this paper, a work in progress system architecture is presented, which aims to implement a continuous production chain for collective cloud manufacturing. Current problems for collective production in the areas of ...
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ISBN:
(纸本)9781538675441
In this paper, a work in progress system architecture is presented, which aims to implement a continuous production chain for collective cloud manufacturing. Current problems for collective production in the areas of cloud manufacturing and computer-aided process planning are listed, which have a particular impact on the individuality and innovative ability of SMEs. To solve these problems, an architectural concept using software containers and an evolutionary needs model is presented. The focus here is on making the decision to collaborate on providing a service in regards to a global demand-model and extending the external commissioning from a single component to the entire production of a product as a demand. Finally, an innovative concept for production process planning for assembly lines using model-based systems engineering approach is presented as an evaluation scenario.
This paper presents the study and analysis of linear, adaptive and predictive controllers for pitch control of Vertical Take-off and Landing System (VTOL). Since VTOL aircraft system is a highly nonlinear system with ...
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The main problems connected with modelling of complex technological systems of greenhouse production are considered. The methodological approaches used at present on the basis of classical comparative analysis with su...
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Wargame can effectively improve the fidelity and efficiency of combat deduction, and has the ability to solve complex military problems. It is theoretical and military significance to carry out the research on the dev...
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ISBN:
(数字)9781728130668
ISBN:
(纸本)9781728130675
Wargame can effectively improve the fidelity and efficiency of combat deduction, and has the ability to solve complex military problems. It is theoretical and military significance to carry out the research on the development and application of computer wargame system. In this paper, the method of knowledge representation and reasoning of fuzzy Petri nets is applied to the strategy of wargame deduction. The characteristics of the graphs are used to represent different variables with different symbols, which can form a concise PN map. This PN map can be used for the force representation and reasoning strategy in the wargame system. The results show that the Petri net-based knowledge representation and reasoning algorithm is very effective for the wargame strategy.
Many power networks are currently under major change processes due to the necessary integration of renewable energy sources. This brings the need to include Active Power Filter (APF) as well as controlling them in an ...
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This paper investigates the usage of a distributed algorithm - the alternative direction method of multipliers for control of system of systems, i.e. control of a complex system comprising large number of distributed ...
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ISBN:
(纸本)9789532330953
This paper investigates the usage of a distributed algorithm - the alternative direction method of multipliers for control of system of systems, i.e. control of a complex system comprising large number of distributed and partially autonomous subsystems. The control algorithm is based on parametrization and decomposition of the central optimization problem into local optimization problems specific to individual subsystems, while taking into account the coupling constraints that link them. Local problems are solved offline using multi-parametric optimization methods, whereas the coordination problem is solved online at every sampling step and the optimal solution is applied to the system at hand in a receding horizon fashion. The method solves the optimal control problem online iteratively while exploiting the control system structure. The efficiency of the method is tested on a number of generated distributed optimization problemsmodeling large systems of systems.
Several systems are integrated in passenger cars. Some of them are just redundant systems due to safety requirements. Others, are completely different and can interact with each other as long as they are operating ins...
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ISBN:
(纸本)9781538670255
Several systems are integrated in passenger cars. Some of them are just redundant systems due to safety requirements. Others, are completely different and can interact with each other as long as they are operating inside the same vehicle. control allocation methods have been successfully implemented in advanced aircrafts to avoid conflicts, especially in the context of redundant systems. In this paper, we will rather focus on coordinating non-redundant advanced chassis systems with different dynamics. This difference in dynamics can be especially problematic when systems exhibit different communication delays. Model Predictive control Allocation (MPCA) methods are therefore investigated in order to activate the right system at the right moment. Results show that particularly when the most effective system is saturated, another system with a different time delay can be activated few steps before saturation to instantly take over the maneuver. With good knowledge of actuator dynamics and higher computation power, MPCA methods are able to solve complexproblems in severe situations.
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