Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Shaokun Jin"'
Publikováno v:
Applied Sciences, Vol 9, Iss 10, p 2105 (2019)
The method of simultaneous localization and mapping (SLAM) using a light detection and ranging (LiDAR) sensor is commonly adopted for robot navigation. However, consumer robots are price sensitive and often have to use low-cost sensors. Due to the po
Externí odkaz:
https://doaj.org/article/25adbff474b64266a1866d0c84ef5c2e
Publikováno v:
Applied Sciences, Vol 9, Iss 7, p 1366 (2019)
The depth estimation of the 3D deformable object has become increasingly crucial to various intelligent applications. In this paper, we propose a feature-based approach for accurate depth estimation of a deformable 3D object with a single camera, whi
Externí odkaz:
https://doaj.org/article/fb869fcb71f842c2a5bae61a83cc6f26
Publikováno v:
IEEE Transactions on Systems, Man, and Cybernetics: Systems. 49:1175-1185
The approach of dynamical system (DS) is promising for modeling robot motion, and provides a flexible means of realizing robot learning and control. Accuracy, stability, and learning speed are the three main factors to be considered when learning rob
Autor:
Yongsheng Ou, Shaokun Jin
Publikováno v:
Applied Sciences
Volume 9
Issue 24
Volume 9
Issue 24
In order to enable robots to be more intelligent and flexible, one way is to let robots learn human control strategy from demonstrations. It is a useful methodology, in contrast to traditional preprograming methods, in which robots are required to sh
Publikováno v:
ROBIO
Estimating 6D poses of objects from RGB images is very crucial for robots to interact with the surrounding environment and to cooperate with humans. It is a challenging problem due to the various shapes of objects, the occlusions among objects, as we
Publikováno v:
IROS
Learning from Demonstration (LfD) has been identified as an effective method for making robots adapt to a similar kind of tasks. In this work, a framework of learning from demonstration has been proposed for modelling robot motions. We present an app
Publikováno v:
IEEE transactions on neural networks and learning systems. 30(12)
Learning from demonstration (LfD) has been increasingly used to encode robot tasks such that robots can achieve reproduction more flexibly in unstructured environments (e.g., households or factories). It is an effective alternative to preprogramming
Autor:
Shaokun Jin, Yongsheng Ou
Publikováno v:
Social Robotics ISBN: 9783030052034
ICSR
ICSR
Dynamic 3D object reconstruction becomes increasingly crucial to various intelligent applications. Most existing algorithms, in spite of the accurate performances, have the problems of high cost and complex computations. In this paper, we propose a n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::73f6a08b764eb78f8d760abc48f471cc
https://doi.org/10.1007/978-3-030-05204-1_37
https://doi.org/10.1007/978-3-030-05204-1_37
Publikováno v:
RCAR
This paper attempts to build a novel model for robots to undertake obstacle avoidance tasks. Conventional work mainly forms a dynamical system (DS) through learning. The dynamical system learned from given demonstrations thus control the robot to per
Publikováno v:
2016 12th World Congress on Intelligent Control and Automation (WCICA).
The technique of tuning a cavity filter is purely a rule of thumb: only experienced tuning engineer is competent to the task. However, with the great development of the communication industry and the rapid increasing of production capacity, the need