Search results

1 – 2 of 2
Article
Publication date: 19 June 2017

Bo Sun, Yadan Zeng, Houde Dai, Junhao Xiao and Jianwei Zhang

This paper aims to present the spherical entropy image (SEI), a novel global descriptor for the scan registration of three-dimensional (3D) point clouds. This paper also…

Abstract

Purpose

This paper aims to present the spherical entropy image (SEI), a novel global descriptor for the scan registration of three-dimensional (3D) point clouds. This paper also introduces a global feature-less scan registration strategy based on SEI. It is advantageous for 3D data processing in the scenarios such as mobile robotics and reverse engineering.

Design/methodology/approach

The descriptor works through representing the scan by a spherical function named SEI, whose properties allow to decompose the six-dimensional transformation into 3D rotation and 3D translation. The 3D rotation is estimated by the generalized convolution theorem based on the spherical Fourier transform of SEI. Then, the translation recovery is determined by phase only matched filtering.

Findings

No explicit features and planar segments should be contained in the input data of the method. The experimental results illustrate the parameter independence, high reliability and efficiency of the novel algorithm in registration of feature-less scans.

Originality/value

A novel global descriptor (SEI) for the scan registration of 3D point clouds is presented. It inherits both descriptive power of signature-based methods and robustness of histogram-based methods. A high reliability and efficiency registration method of scans based on SEI is also demonstrated.

Details

Industrial Robot: An International Journal, vol. 44 no. 4
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 8 January 2018

Yu-Shan Su, Zong-Xi Zheng and Jin Chen

Innovation ecosystem is an emerging and popular concept in both academic and industrial circles. It offers a new perspective for enterprise strategy positioning. A business can…

3573

Abstract

Purpose

Innovation ecosystem is an emerging and popular concept in both academic and industrial circles. It offers a new perspective for enterprise strategy positioning. A business can create more value through a healthy innovation ecosystem. The paper aims to discuss these issues.

Design/methodology/approach

In this paper, the authors utilize a new triple-layer core-periphery framework to analyze Insigma Group’s multi-platform collaboration innovation ecosystem, in order to explore the architecture and heterogeneous functions inside an innovation ecosystem.

Findings

The authors illustrate the components and working mechanisms of the four platforms, which function as ideation, entrepreneurship, financing and investment, and innovation, inside Insigma’s innovation ecosystem in detail, and explain how they interact and collaborate toward a shared aim of the whole innovation ecosystem.

Research limitations/implications

The innovation ecosystem is an emerging concept. In this study, the authors combined two existing analytical frameworks of innovation ecosystem, and proposed a triple-layer core-periphery framework, which enable us to analyze the heterogeneity inside an innovation ecosystem.

Practical implications

The authors discussed the role of government and its policies in shaping the innovation ecosystem at the enterprise level.

Originality/value

The authors believe that this paper provides a holistic study of Insigma’s innovation ecosystem. The triple-layer core-periphery framework can be used to study other enterprise innovation ecosystem in the future.

Details

Management Decision, vol. 56 no. 1
Type: Research Article
ISSN: 0025-1747

Keywords

1 – 2 of 2