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pro vyhledávání: '"Yang, Simon X"'
This paper addresses the challenges of distributed formation control in multiple mobile robots, introducing a novel approach that enhances real-world practicability. We first introduce a distributed estimator using a variable structure and cascaded d
Externí odkaz:
http://arxiv.org/abs/2403.15716
Autor:
Li, Junfei, Yang, Simon X.
Natural disasters and urban accidents drive the demand for rescue robots to provide safer, faster, and more efficient rescue trajectories. In this paper, a feature learning-based bio-inspired neural network (FLBBINN) is proposed to quickly generate a
Externí odkaz:
http://arxiv.org/abs/2403.08238
Autor:
Li, Junfei, Yang, Simon X.
Fish schools present high-efficiency group behaviors through simple individual interactions to collective migration and dynamic escape from the predator. The school behavior of fish is usually a good inspiration to design control architecture for swa
Externí odkaz:
http://arxiv.org/abs/2402.04228
Autor:
Zhu, Danjie, Yang, Simon X.
The paper presents an innovative approach (CBNNTAP) that addresses the complexities and challenges introduced by ocean currents when optimizing target assignment and motion planning for a multi-unmanned underwater vehicle (UUV) system. The core of th
Externí odkaz:
http://arxiv.org/abs/2401.05521
Autor:
Li, Junfei, Yang, Simon X.
Intelligent escape is an interdisciplinary field that employs artificial intelligence (AI) techniques to enable robots with the capacity to intelligently react to potential dangers in dynamic, intricate, and unpredictable scenarios. As the emphasis o
Externí odkaz:
http://arxiv.org/abs/2310.14485
Robust constrained formation tracking control of underactuated underwater vehicles (UUVs) fleet in three-dimensional space is a challenging but practical problem. To address this problem, this paper develops a novel consensus based optimal coordinati
Externí odkaz:
http://arxiv.org/abs/2308.09326
This paper addresses distributed robust learning-based control for consensus formation tracking of multiple underwater vessels, in which the system parameters of the marine vessels are assumed to be entirely unknown and subject to the modeling mismat
Externí odkaz:
http://arxiv.org/abs/2308.09320
Collaboration is one of the most important factors in multi-robot systems. Considering certain real-world applications and to further promote its development, we propose a new benchmark to evaluate multi-robot collaboration in Target Trapping Environ
Externí odkaz:
http://arxiv.org/abs/2308.08862
Autor:
Liu, Ran, Lau, Billy Pik Lik, Ismail, Khairuldanial, Chathuranga, Achala, Yuen, Chau, Yang, Simon X., Guan, Yong Liang, Mao, Shiwen, Tan, U-Xuan
Simultaneous localization and mapping (SLAM) is paramount for unmanned systems to achieve self-localization and navigation. It is challenging to perform SLAM in large environments, due to sensor limitations, complexity of the environment, and computa
Externí odkaz:
http://arxiv.org/abs/2305.13635
This paper investigated the distributed leader follower formation control problem for multiple differentially driven mobile robots. A distributed estimator is first introduced and it only requires the state information from each follower itself and i
Externí odkaz:
http://arxiv.org/abs/2305.02288