Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Zhong, Fangwei"'
Diplomacy is one of the most sophisticated activities in human society. The complex interactions among multiple parties/ agents involve various abilities like social reasoning, negotiation arts, and long-term strategy planning. Previous AI agents sur
Externí odkaz:
http://arxiv.org/abs/2407.06813
Multi-agent systems (MAS) need to adaptively cope with dynamic environments, changing agent populations, and diverse tasks. However, most of the multi-agent systems cannot easily handle them, due to the complexity of the state and task space. The soc
Externí odkaz:
http://arxiv.org/abs/2405.01839
Embodied visual tracking is to follow a target object in dynamic 3D environments using an agent's egocentric vision. This is a vital and challenging skill for embodied agents. However, existing methods suffer from inefficient training and poor genera
Externí odkaz:
http://arxiv.org/abs/2404.09857
Fast adapting to unknown peers (partners or opponents) with different strategies is a key challenge in multi-agent games. To do so, it is crucial for the agent to probe and identify the peer's strategy efficiently, as this is the prerequisite for car
Externí odkaz:
http://arxiv.org/abs/2402.02468
Autor:
Wang, Hongcheng, Wang, Yuxuan, Zhong, Fangwei, Wu, Mingdong, Zhang, Jianwei, Wang, Yizhou, Dong, Hao
Publikováno v:
The IEEE Robotics and Automation Letters 2023
Visual-audio navigation (VAN) is attracting more and more attention from the robotic community due to its broad applications, \emph{e.g.}, household robots and rescue robots. In this task, an embodied agent must search for and navigate to the sound s
Externí odkaz:
http://arxiv.org/abs/2304.10773
Active Object Tracking (AOT) aims to maintain a specific relation between the tracker and object(s) by autonomously controlling the motion system of a tracker given observations. AOT has wide-ranging applications, such as in mobile robots and autonom
Externí odkaz:
http://arxiv.org/abs/2304.03623
This paper presents a multi-agent reinforcement learning (MARL) scheme for proactive Multi-Camera Collaboration in 3D Human Pose Estimation in dynamic human crowds. Traditional fixed-viewpoint multi-camera solutions for human motion capture (MoCap) a
Externí odkaz:
http://arxiv.org/abs/2303.03767
Learning 3D human pose prior is essential to human-centered AI. Here, we present GFPose, a versatile framework to model plausible 3D human poses for various applications. At the core of GFPose is a time-dependent score network, which estimates the gr
Externí odkaz:
http://arxiv.org/abs/2212.08641
Object Rearrangement is to move objects from an initial state to a goal state. Here, we focus on a more practical setting in object rearrangement, i.e., rearranging objects from shuffled layouts to a normative target distribution without explicit goa
Externí odkaz:
http://arxiv.org/abs/2209.00853
Autor:
Wu, Tianhao, Zhong, Fangwei, Geng, Yiran, Wang, Hongchen, Zhu, Yongjian, Wang, Yizhou, Dong, Hao
Grasping moving objects, such as goods on a belt or living animals, is an important but challenging task in robotics. Conventional approaches rely on a set of manually defined object motion patterns for training, resulting in poor generalization to u
Externí odkaz:
http://arxiv.org/abs/2203.02119