Multi-Drone Collaborative Trajectory Optimization for Large-Scale Aerial 3D Scanning

Due to new circumstances of living, climate and environmental changes, varieties of human body shapes are growing. Therefore, obtaining uniformly clothes for special issues in the group of people with similar interests (dancing groups, choirs, etc.) are getting more and more complex. Besides the self-estimation and perception about the shape and size of the person varies due to different sizing from brand to brand. To dress-up the group of people with different sizes in uniformly way is not an easy task for the supplier – even if the model chosen for the gown is casual, most of the producers doesn’t apply a large scale of sizes. Frequently sizing systems do not fit to the needs of the end-users. Size marked on the clothing describes only some information about body size, if any. Therefore, part of clothing supplied is not suitable for end-user groups, but if already purchased it is decided to discard them. Such a set of circumstances, in contrast to global progress towards sustainable development, which is also based on environmental responsibility, can serve as a contributing factor to further growth in clothing consumption. The main purpose of this study is to make an insight into sizing approaches for a special group of people focusing on the best practice of human body 3D scanning. The paper outlines a certain target group’s understanding of the clothing size correspondence to their individual body characteristics. Advantages of human body scanning for analysing of body characteristics and solving sizing issues are discussed. Within the study, anthropometric data sets of 50 women group were obtained using a 3D scanner to develop the distribution of this special group into size groups and analyse individual body measurements that are significant for the design of appropriate garment patterns. Conclusions made in this paper acknowledge 3D scanning as an advantageous method for anthropometric data obtaining which are determinate for garment design and sizing system development.

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Integrated fringe projection 3D scanning system for large-scale metrology based on laser tracker

AOPC 2017: 3D Measurement Technology for Intelligent Manufacturing ◽

10.1117/12.2285822 ◽

2017 ◽

Author(s):

HUI DU ◽

Xiaobo Chen ◽

Dan Zhou ◽

Gen Guo ◽

Juntong Xi

Keyword(s):

Large Scale ◽

3D Scanning ◽

Fringe Projection ◽

Scanning System ◽

Laser Tracker

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Variational Hilbert regression for terrain modeling and trajectory optimization

The International Journal of Robotics Research ◽

10.1177/0278364919844586 ◽

2019 ◽

Vol 38 (12-13) ◽

pp. 1375-1387 ◽

Cited By ~ 2

Author(s):

Vitor Guizilini ◽

Fabio Ramos

Keyword(s):

Regression Model ◽

Trajectory Optimization ◽

Large Scale ◽

Reproducing Kernel ◽

Reproducing Kernel Hilbert Space ◽

Continuous Model ◽

Model Parameters ◽

Terrain Modeling ◽

Variational Bayesian Inference ◽

Complex Functions

The ability to generate accurate terrain models is of key importance in a wide variety of robotics tasks, ranging from path planning and trajectory optimization to environment exploration and mining applications. This paper introduces a novel regression methodology for terrain modeling that can approximate arbitrarily complex functions based on a series of simple kernel calculations, using variational Bayesian inference. A sparse feature vector is used to efficiently project input points into a high-dimensional reproducing kernel Hilbert space, according to a set of inducing points automatically generated from clustering available data. Each inducing point maintains its own regression model in addition to individual kernel parameters, and the entire set is iteratively optimized as more data are collected in order to maximize a global variational lower bound. We also show how kernel and regression model parameters can be jointly learned, to achieve a better approximation of the underlying function. Experimental results show that the proposed methodology consistently outperforms current state-of-the-art techniques, while producing a continuous model with a fully probabilistic treatment of uncertainties, well-defined gradients, and highly scalable to large-scale datasets. As a practical application of the proposed terrain modeling technique, we explore the problem of trajectory optimization, deriving gradients that allow the efficient generation of continuous paths using standard optimization algorithms, minimizing a series of useful properties (i.e. distance traveled, changes in elevation, and terrain variance).

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Trajectory Optimization Using Analytical Target Cascading

Journal of Mechanical Design ◽

10.1115/1.4037714 ◽

2017 ◽

Vol 139 (12) ◽

Author(s):

Xiang Li ◽

Xiaonpeng Wang ◽

Houjun Zhang ◽

Yuheng Guo

Keyword(s):

Trajectory Optimization ◽

Large Scale ◽

Optimization Problems ◽

Sparse Matrix ◽

Functional Dependence ◽

Analytical Target Cascading ◽

Scale Problem ◽

Direct Collocation ◽

Target Cascading ◽

Direct Collocation Method

In the previous reports, analytical target cascading (ATC) is generally applied to product optimization. In this paper, the application area of ATC is expanded to trajectory optimization. Direct collocation method is utilized to convert a trajectory optimization into a nonlinear programing (NLP) problem. The converted NLP is a large-scale problem with sparse matrix of functional dependence table (FDT) suitable for the application of ATC. Three numerical case studies are provided to show the effects of ATC in solving trajectory optimization problems.

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Submodular Trajectory Optimization for Aerial 3D Scanning

2017 IEEE International Conference on Computer Vision (ICCV) ◽

10.1109/iccv.2017.569 ◽

2017 ◽

Cited By ~ 26

Author(s):

Mike Roberts ◽

Shital Shah ◽

Debadeepta Dey ◽

Anh Truong ◽

Sudipta Sinha ◽

...

Keyword(s):

Trajectory Optimization ◽

3D Scanning

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