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A multichannel human-swarm robot interaction system in augmented reality

DOI:10.3724/SP.J.2096-5796.20.00014

Available Online:2020-05-29

Abstract (11) | PDF (2) | HTML (8)
Background
A large number of robots have put forward the new requirements for human-robot interaction. One of the problems in human-swarm robot interaction is how to naturally achieve an efficient and accurate interaction between humans and swarm robot systems. To address this, this paper proposes a new type of human-swarm natural interaction system.
Methods
Through the cooperation between three-dimensional (3D) gesture interaction channel and natural language instruction channel, a natural and efficient interaction between a human and swarm robots is achieved.
Results
First, A 3D lasso technology realizes a batch-picking interaction of swarm robots through oriented bounding boxes. Second, control instruction labels for swarm-oriented robots are defined. The instruction label is integrated with the 3D gesture and natural language through instruction label filling. Finally, the understanding of natural language instructions is realized through a text classifier based on the maximum entropy model. A head-mounted augmented reality display device is used as a visual feedback channel.
Conclusions
The experiments on selecting robots verify the feasibility and availability of the system.
Summary study of data-driven photometric stereo methods

DOI:10.3724/SP.J.2096-5796.20.00009

Available Online:2020-05-22

Abstract (39) | PDF (10) | HTML (27)
Background
A photometric stereo method aims to recover the surface normal of a 3D object observed under varying light directions. It is an ill-defined problem because the general reflectance properties of the surface are unknown.
Methods
This paper reviews existing data-driven methods, with a focus on their technical insights into the photometric stereo problem. We divide these methods into two categories, per-pixel and all-pixel, according to how they process an image. We discuss the differences and relationships between these methods from the perspective of inputs, networks, and data, which are key factors in designing a deep learning approach.
Results
We demonstrate the performance of the models using a popular benchmark dataset.
Conclusions
Data-driven photometric stereo methods have shown that they possess a superior performance advantage over traditional methods. However, these methods suffer from various limitations, such as limited generalization capability. Finally, this study suggests directions for future research.
Object registration using an RGB-D camera for complex product augmented assembly guidance

DOI:10.3724/SP.J.2096-5796.19.00006

Available Online:2020-05-19

Abstract (47) | PDF (7) | HTML (50)
Background
Augmented assembly guidance aims to help users complete assembly operations more efficiently and quickly through augmented reality technology, breaking the limitations of traditional assembly guidance technology which is single in content and boring in way. Object registration is one of the key technologies in augmented assembly guidance process, which can affect the location and direction of virtual assembly guidance information in real assembly environment.
Methods
This paper presents an object registration method based on RGB-D camera, which combines Lucas-Kanade (LK) optical flow algorithm and Iterative Closet Point (ICP) algorithm. An augmented assembly guidance system for complex products through this method is built. Meanwhile, in order to compare the effectiveness of the proposed method, we also implemented object registration based on an open source augmented reality SDK Vuforia.
Results
An engine model and a complex weapon cabin equipment are taken as an case to verify this work. The result shows that the registration method proposed in this paper is more accurate and stable compared with that based on Vuforia and the augmented assembly guidance system through this method greatly improves the user's time compared with the traditional assembly.
Conclusions
Therefore, we can conclude that the object registration method mentioned in this paper can be well applied in the augmented assembly guidance system, which can do enhance the efficiency of assembly considerably.
Interactive free-viewpoint video generation

DOI:10.3724/SP.J.2096-5796.20.00013

Available Online:2020-04-29

Abstract (44) | PDF (6) | HTML (34)
Background
Free-viewpoint video (FVV) is processed video content in which viewers can freely select the viewing position and angle. FVV delivers an improved visual experience and can also help synthesize special effects and virtual reality content. In this paper, a complete FVV system is proposed to interactively control the viewpoints of video relay programs through multimedia terminals such as computers and tablets.
Methods
The hardware of the FVV generation system is a set of synchronously controlled cameras, and the software generates videos in novel viewpoints from the captured video using view interpolation. The interactive interface is designed to visualize the generated video in novel viewpoints and enable the viewpoint to be changed interactively.
Results
Experiments show that our system can synthesize plausible videos in intermediate viewpoints with a view range of up to 180°.