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This paper presents a new method to automate robot motion planning in automotive manufacturing environments. A general framework is developed for CAD‐guided robot motion…
This paper presents a new method to automate robot motion planning in automotive manufacturing environments. A general framework is developed for CAD‐guided robot motion planning. The problem is formulated as a constraint‐satisfying problem of tool configurations or, robot hand poses. Two types of robot motion are considered: discrete motion, or point to point motion, and continuous motion. Triangular facets are used to approximate the part surfaces. A pre‐partition process decomposes the complex part surfaces into several simple, easy‐to‐solve patches. For each patch, robot hand poses are determined to satisfy certain task constraints. In this paper, the approach is applied to two applications: vision sensor planning and spray painting gun path planning. It is our belief that more robot planning applications in manufacturing can benefit from this method.
Automatic trajectory generation for spray painting is highly desirable for today’s automotive manufacturing. Generating paint gun trajectories for free‐form surfaces to…
Automatic trajectory generation for spray painting is highly desirable for today’s automotive manufacturing. Generating paint gun trajectories for free‐form surfaces to satisfy paint thickness requirements is still highly challenging due to the complex geometry of free‐form surfaces. In this paper, a CAD‐guided paint gun trajectory generation system for free‐form surfaces has been developed. The system utilizes the CAD information of a free‐form surface to be painted and a paint gun model to generate a paint gun trajectory to satisfy the paint thickness requirements. A paint thickness verification method is also provided to verify the generated trajectories. The simulation results have shown that the trajectory generation system achieves satisfactory performance. This trajectory generation system can also be applied to generate trajectories for many other CAD‐guided robot trajectory planning applications.
The purpose of this paper is to analyze the influencing factors of new logistics service product design (NLSPD) in China to establish a theoretical framework for the…
The purpose of this paper is to analyze the influencing factors of new logistics service product design (NLSPD) in China to establish a theoretical framework for the future development of the logistics industry.
The paper adopts the multi-case study method based on a sample of four Chinese logistics enterprises, in which the authors consider the logistics service maturity (LSM), a distinct characteristic of logistics enterprises.
NLSPD is directly related to the degree of supply–demand matching (SDM) and LSM. Customer demand, service capability and peer competition influence the performance of NLSPD through the SDM degree, whereas LSM moderates these influencing mechanisms. Moreover, the degree of SDM has a positive impact on LSM.
The findings can help the managers of logistics enterprises and practitioners in the logistics industry understand the complexity of NLSPD. First, they should broaden and deepen their service offering to enhance the degree of LSM. Second, they should pay attention to the factors that affect SDM systematically. Finally, it is vital to balance the relationship between LSM and SDM.
NLSPD has become an important tool affecting the competitiveness and sustainability of logistics service enterprises. This is the first paper to propose a theoretical framework for NLSPD that considers the characteristic of the logistics industry. It clarifies the mechanisms of influencing factors, and contributes to the literature by filling the research gap.
The purpose of the present study is to use an amino-functional polysiloxane for the surface modification of red iron oxide (Fe2O3) pigment particles for their improved…
The purpose of the present study is to use an amino-functional polysiloxane for the surface modification of red iron oxide (Fe2O3) pigment particles for their improved dispersion stability and hydrophobicity and to study the chemical interactions of polysiloxanes with the particle surface.
Surface-treated red Fe2O3 pigment particles were prepared by treatment of the particles with different quantities of the (aminopropylmethylsiloxane)-dimethylsiloxane copolymer in concentrated suspensions in water. The samples were analysed with different instrumental and spectroscopic techniques to study the interaction of the polysiloxane with the particle surface and the effect of the surface treatment of the particles on their dispersion stability and hydrophobicity.
Chemisorption of the amino-polysiloxane onto the surface of Fe2O3 particles resulted in stable layers which turned out to be helpful in improving greatly the dispersion stability of the particles as shown by the Static Light Scattering and Dynamic Light Scattering results. Formation of a polysiloxane coating onto the surface of the pigment particles was confirmed by studying the interactions of the polymer molecules with Fe2O3 surfaces by Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy techniques.
The surface-treated red Fe2O3 particles with improved dispersion stability can be important components of various formulations in applications such as the colouring of the cement or inorganic pigment-based paint formulations.
The study provides mechanistic insights about the interactions of amino-polysiloxane with the red Fe2O3 particles. The process of surface modification of red Fe2O3 particles with the amino-functional polysiloxane showed increased hydrophobicity and dispersion stability which is an important requirement of the pigment-based formulations in real applications.
We make use of the Volunteered Geographic Information (VGI) data to extract the total extent of the roads using remote sensing images. VGI data is often provided only as…
We make use of the Volunteered Geographic Information (VGI) data to extract the total extent of the roads using remote sensing images. VGI data is often provided only as vector data represented by lines and not as full extent. Also, high geolocation accuracy is not guaranteed and it is common to observe misalignment with the target road segments by several pixels on the images. In this work, we use the prior information provided by the VGI and extract the full road extent even if there is significant mis-registration between the VGI and the image. The method consists of image segmentation and traversal of multiple agents along available VGI information. First, we perform image segmentation, and then we traverse through the fragmented road segments using autonomous agents to obtain a complete road map in a semi-automatic way once the seed-points are defined. The road center-line in the VGI guides the process and allows us to discover and extract the full extent of the road network based on the image data. The results demonstrate the validity and good performance of the proposed method for road extraction that reflects the actual road width despite the presence of disturbances such as shadows, cars and trees which shows the efficiency of the fusion of the VGI and satellite images.