Zobrazeno 1 - 10
of 239
pro vyhledávání: '"Xiaogang Ruan"'
Publikováno v:
Biomimetics, Vol 9, Iss 6, p 315 (2024)
The traditional Model-Based Reinforcement Learning (MBRL) algorithm has high computational cost, poor convergence, and poor performance in robot spatial cognition and navigation tasks, and it cannot fully explain the ability of animals to quickly ada
Externí odkaz:
https://doaj.org/article/715f8ec6d0574fa2a7bacd7cd1049e14
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-22 (2022)
Abstract Target-driven visual navigation is essential for many applications in robotics, and it has gained increasing interest in recent years. In this work, inspired by animal cognitive mechanisms, we propose a novel navigation architecture that sim
Externí odkaz:
https://doaj.org/article/7da595c7c85449abad744859a691f618
Publikováno v:
IEEE Access, Vol 8, Pp 2590-2598 (2020)
Data association is the foundation of state estimation in mobile robot simultaneous localization and mapping. Aiming at the problems of false association, high computational complexity in joint compatible branch and bound algorithm, we propose an opt
Externí odkaz:
https://doaj.org/article/1c9e3ac926d04732abfb32a66dab1645
Publikováno v:
IEEE Access, Vol 8, Pp 178117-178129 (2020)
Simulating biological intelligence has been proved to be an effective way to design intelligent robots, and simultaneously can solve the problems existing in machine learning methods. For creatures, their motor skills achieving is the first stage of
Externí odkaz:
https://doaj.org/article/e5a6fcbc3bf74fd389bac9476cb1f087
Publikováno v:
Brain Sciences, Vol 12, Iss 9, p 1176 (2022)
Since the hippocampus plays an important role in memory and spatial cognition, the study of spatial computation models inspired by the hippocampus has attracted much attention. This study relies mainly on reward signals for learning environments and
Externí odkaz:
https://doaj.org/article/d5e2422ebd684bf7970296f153d483cf
Publikováno v:
Machines, Vol 10, Iss 8, p 703 (2022)
In the crowd navigation, reinforcement learning based on graph neural network is a promising method, which effectively solves the poor navigation effect based on social interaction model and the freezing behavior of robot in extreme cases. However, s
Externí odkaz:
https://doaj.org/article/770d0d639a734f4b87362ba42a317334
Publikováno v:
Applied Sciences, Vol 12, Iss 9, p 4695 (2022)
Algorithms such as RRT (Rapidly exploring random tree), A* and their variants have been widely used in the field of robot path planning. A lot of work has shown that these detectors are unable to carry out effective and stable results for moving obje
Externí odkaz:
https://doaj.org/article/5114cf5f1e554c4db9f57eb341ae48f6
Publikováno v:
Brain Sciences, Vol 11, Iss 6, p 803 (2021)
Neurophysiological studies have shown that the hippocampus, striatum, and prefrontal cortex play different roles in animal navigation, but it is still less clear how these structures work together. In this paper, we establish a navigation learning mo
Externí odkaz:
https://doaj.org/article/e5fc3b233bd6477d86bb5d5d540de312
Publikováno v:
Sensors, Vol 19, Iss 7, p 1624 (2019)
Low-cost microelectro mechanical systems (MEMS)-based inertial measurement unit (IMU) measurements are usually affected by inaccurate scale factors, axis misalignments, and g-sensitivity errors. These errors may significantly influence the performanc
Externí odkaz:
https://doaj.org/article/43eea236bc194f9ca2985c1442824d61
Publikováno v:
Sensors, Vol 16, Iss 12, p 2171 (2016)
Noise and constant empirical motion constraints affect the extraction of distinctive spatiotemporal features from one or a few samples per gesture class. To tackle these problems, an adaptive local spatiotemporal feature (ALSTF) using fused RGB-D dat
Externí odkaz:
https://doaj.org/article/d26c075cec4c4c6c9f3b0fb1b9c120fb