Výsledky vyhledávání - "Zhang, Tingrui"

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Implicit Swept Volume SDF: Enabling Continuous Collision-Free Trajectory Generation for Arbitrary Shapes

Autor: Wang, Jingping, Zhang, Tingrui, Zhang, Qixuan, Zeng, Chuxiao, Yu, Jingyi, Xu, Chao, Xu, Lan, Gao, Fei

In the field of trajectory generation for objects, ensuring continuous collision-free motion remains a huge challenge, especially for non-convex geometries and complex environments. Previous methods either oversimplify object shapes, which results in

Externí odkaz: http://arxiv.org/abs/2405.00362

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Continuous Implicit SDF Based Any-shape Robot Trajectory Optimization

Autor: Zhang, Tingrui, Wang, Jingping, Xu, Chao, Gao, Alan, Gao, Fei

Optimization-based trajectory generation methods are widely used in whole-body planning for robots. However, existing work either oversimplifies the robot's geometry and environment representation, resulting in a conservative trajectory, or suffers f

Externí odkaz: http://arxiv.org/abs/2303.01330

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Dissertation/ Thesis

Performance Analysis Of Massive MIMO With Port Reduction

Autor: Zhang, Tingrui

In centralized radio access network (C-RAN) architecture, the base-band unit (BBU) is connected to one or more remote radio units (RRUs) via a fronthaul (FH) interface. Upgrading base station antennas in C-RAN to support massive multiple-input multip

Externí odkaz: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-323527

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Decentralized Planning for Car-Like Robotic Swarm in Cluttered Environments

Autor: Ma, Changjia, Han, Zhichao, Zhang, Tingrui, Wang, Jingping, Xu, Long, Li, Chengyang, Xu, Chao, Gao, Fei

Robot swarm is a hot spot in robotic research community. In this paper, we propose a decentralized framework for car-like robotic swarm which is capable of real-time planning in cluttered environments. In this system, path finding is guided by enviro

Externí odkaz: http://arxiv.org/abs/2210.05863

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Robust and Efficient Trajectory Planning for Formation Flight in Dense Environments

Autor: Quan, Lun, Yin, Longji, Zhang, Tingrui, Wang, Mingyang, Wang, Ruilin, Zhong, Sheng, Xin, Zhou, Cao, Yanjun, Xu, Chao, Gao, Fei

Formation flight has a vast potential for aerial robot swarms in various applications. However, existing methods lack the capability to achieve fully autonomous large-scale formation flight in dense environments. To bridge the gap, we present a compl

Externí odkaz: http://arxiv.org/abs/2210.04048

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