Zobrazeno 1 - 10
of 112
pro vyhledávání: '"Nishimura, Mai"'
Many sexually mature females suffer from premenstrual syndrome (PMS), but effective coping methods for PMS are limited due to the complexity of symptoms and unclear pathogenesis. Awareness has shown promise in alleviating PMS symptoms but faces chall
Externí odkaz:
http://arxiv.org/abs/2405.05712
Robot swarms hold immense potential for performing complex tasks far beyond the capabilities of individual robots. However, the challenge in unleashing this potential is the robots' limited sensory capabilities, which hinder their ability to detect a
Externí odkaz:
http://arxiv.org/abs/2404.16309
Autor:
Ichihashi, Sosuke, Kuroki, So, Nishimura, Mai, Kasaura, Kazumi, Hiraki, Takefumi, Tanaka, Kazutoshi, Yoshida, Shigeo
The human brain's plasticity allows for the integration of artificial body parts into the human body. Leveraging this, embodied systems realize intuitive interactions with the environment. We introduce a novel concept: embodied swarm robots. Swarm ro
Externí odkaz:
http://arxiv.org/abs/2402.15830
Due to the complex interactions between agents, learning multi-agent control policy often requires a prohibited amount of data. This paper aims to enable multi-agent systems to effectively utilize past memories to adapt to novel collaborative tasks i
Externí odkaz:
http://arxiv.org/abs/2312.02008
Autor:
Nishimura, Mai
甲第24726号
情博第814号
新制||情||137(附属図書館)
学位規則第4条第1項該当
Doctor of Informatics
Kyoto University
DFAM
情博第814号
新制||情||137(附属図書館)
学位規則第4条第1項該当
Doctor of Informatics
Kyoto University
DFAM
Externí odkaz:
http://hdl.handle.net/2433/283845
Multi-robot navigation is the task of finding trajectories for a team of robotic agents to reach their destinations as quickly as possible without collisions. In this work, we introduce a new problem: fair-delay multi-robot navigation, which aims not
Externí odkaz:
http://arxiv.org/abs/2305.11465
The hierarchy of global and local planners is one of the most commonly utilized system designs in autonomous robot navigation. While the global planner generates a reference path from the current to goal locations based on the pre-built map, the loca
Externí odkaz:
http://arxiv.org/abs/2304.12046
We propose a novel method for joint estimation of shape and pose of rigid objects from their sequentially observed RGB-D images. In sharp contrast to past approaches that rely on complex non-linear optimization, we propose to formulate it as a neural
Externí odkaz:
http://arxiv.org/abs/2303.13477
We introduce an on-ground Pedestrian World Model, a computational model that can predict how pedestrians move around an observer in the crowd on the ground plane, but from just the egocentric-views of the observer. Our model, InCrowdFormer, fully lev
Externí odkaz:
http://arxiv.org/abs/2303.09534
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence 37(5) (2023) 6183-6191
Multi-agent path planning (MAPP) is the problem of planning collision-free trajectories from start to goal locations for a team of agents. This work explores a relatively unexplored setting of MAPP where streams of agents have to go through the start
Externí odkaz:
http://arxiv.org/abs/2301.10910