Developing a service robot

Iwashita, S.; Murase, Yuichi; Yasukawa, Yusuke; Kanda, Shigenobu; Sawasaki, Naoyuki; Asada, T.

doi:10.1109/icma.2005.1626698

Cited by 7 publications

(4 citation statements)

References 6 publications

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“…3D reconstruction technology mainly obtains data information such as laser point cloud and images through laser scanning or cameras, then analyzes and processes the obtained data information, and uses 3D reconstruction related methods to model and reproduce scenes in the real world. It has been widely used in the fields of 3D real scene [1][2][3], digital twin [4][5][6], virtual reality [7,8], artificial intelligence [9][10][11], automatic driving [12][13][14], Indoor Robots [15][16][17][18], Outdoor Robots [19][20][21][22][23], UAV Applications [24][25][26][27], 3D printing [28] and so on.…”

Section: Introductionmentioning

confidence: 99%

Overview of image-based 3D reconstruction technology

Niu,

Liu,

Huang

et al. 2024

J. Eur. Opt. Society-Rapid Publ.

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Three-dimensional(3D) reconstruction technology is the key technology to establish and express the objective world by using computer, and it is widely used in real 3D, automatic driving, aerospace, navigation and industrial robot applications. According to different principles, it is mainly divided into methods based on traditional multi-view geometry and methods based on deep learning. This paper introduces the above methods from the perspective of three-dimensional space representation. The feature extraction and stereo matching theory of traditional 3D reconstruction methods are the theoretical basis of 3D reconstruction methods based on deep learning, so the paper focuses on them. With the development of traditional 3D reconstruction methods and the development of deep learning related theories, the explicit deep learning 3D reconstruction method represented by MVSNet and the implicit 3D reconstruction method represented by NeRF have been gradually developed. At the same time, the dataset and evaluation indicators for 3D reconstruction were introduced. Finally, a summary of image based 3D reconstruction was provided. Deep networks based on deep learning have been widely used in computer vision, especially the application of deep learning in depth networks of depth estimation, which will eventually realize real-time pixel-level reconstruction of 3D scenes at different scales.

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Section: Introductionmentioning

confidence: 99%

Overview of image-based 3D reconstruction technology

Niu,

Liu,

Huang

et al. 2024

J. Eur. Opt. Society-Rapid Publ.

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“…With the improvement of domestic living standards, it gradually entered China. Many universities in the country have done a lot of research on clean robots and achieved some results, especially in the robot movement planning and control, which laid the foundation for the research and development of cleaning robot [1] . Foreign intelligent cleaning robot compared to domestic, better performance, and many have a high degree of intelligent design, but the price is generally high, which makes foreign products can not meet the needs of more Chinese ordinary family.…”

Section: Introductionmentioning

confidence: 99%

The Design of Intelligent Cleaning Robot

Wang¹,

Xiao²,

Xin³

et al. 2017

Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)

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Abstract. The purpose of this thesis is to design and produce a low cost, low energy consumption, easy to use, suitable for family life, can realize the automatic cleaning of the intelligent cleaning robot. This design adopts the structured design principle, the design of intelligent cleaning robot based on MSP430 microcontroller is divided into 6 modules: cleaning function module, motion control module, human-computer interaction module, security detection module, route planning module, power supply module. This design uses one button operation method, through the infrared sensor intelligent obstacle avoidance, the installation of bilateral brush and vacuum cleaners cleaning. After experiment, it is proved that the design is reasonable and feasible.

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“…Such as medical robots, rescue robot, police robots, etc. [1][2] However, only a few robots are serviced for household, such as autonomous lawn mower robot, cleaning robot.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of an Intelligent Cleaning Robot Based on Fuzzy Control

Liu

2014

AMR

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Nowadays, intelligent cleaning robot is widely used in housecleaning, hotel and office for cleaning in a half--automatic way or full--automatic way. In recent years, the development of cleaning robot has brought increasing attention in overseas and domestic, and it has become a new development area in the field of service robots. This paper designs an intelligent cleaning robot, which could realize move freely under the control of obstacle avoidance strategies based on the fuzzy logic. According to the information of obstacles from the sensor system, the obstacle avoidance system is built by the fuzzy control method to make the cleaning robot avoid the obstacles autonomously.

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Developing a service robot

Cited by 7 publications

References 6 publications

Overview of image-based 3D reconstruction technology

Overview of image-based 3D reconstruction technology

The Design of Intelligent Cleaning Robot

Design and Implementation of an Intelligent Cleaning Robot Based on Fuzzy Control

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