Zobrazeno 1 - 10
of 636
pro vyhledávání: '"Mu, Yao"'
Visual navigation tasks are critical for household service robots. As these tasks become increasingly complex, effective communication and collaboration among multiple robots become imperative to ensure successful completion. In recent years, large l
Externí odkaz:
http://arxiv.org/abs/2407.00632
Dual-arm robots offer enhanced versatility and efficiency over single-arm counterparts by enabling concurrent manipulation of multiple objects or cooperative execution of tasks using both arms. However, effectively coordinating the two arms for compl
Externí odkaz:
http://arxiv.org/abs/2406.09953
Learning reward functions remains the bottleneck to equip a robot with a broad repertoire of skills. Large Language Models (LLM) contain valuable task-related knowledge that can potentially aid in the learning of reward functions. However, the propos
Externí odkaz:
http://arxiv.org/abs/2405.07162
Autor:
Yu, Qiaojun, Hao, Ce, Wang, Junbo, Liu, Wenhai, Liu, Liu, Mu, Yao, You, Yang, Yan, Hengxu, Lu, Cewu
Robotic manipulation in everyday scenarios, especially in unstructured environments, requires skills in pose-aware object manipulation (POM), which adapts robots' grasping and handling according to an object's 6D pose. Recognizing an object's positio
Externí odkaz:
http://arxiv.org/abs/2403.13365
The Russia-Ukraine conflict is a growing concern worldwide and poses serious threats to regional and global food security. Using monthly trade data for maize, rice, and wheat from 2016/1 to 2022/12, this paper constructs three international crop trad
Externí odkaz:
http://arxiv.org/abs/2403.12496
Autor:
Ma, Ji, Dai, Hongming, Mu, Yao, Wu, Pengying, Wang, Hao, Chi, Xiaowei, Fei, Yang, Zhang, Shanghang, Liu, Chang
Zero-Shot Object Navigation (ZSON) requires agents to autonomously locate and approach unseen objects in unfamiliar environments and has emerged as a particularly challenging task within the domain of Embodied AI. Existing datasets for developing ZSO
Externí odkaz:
http://arxiv.org/abs/2402.19007
Autor:
Mu, Yao, Chen, Junting, Zhang, Qinglong, Chen, Shoufa, Yu, Qiaojun, Ge, Chongjian, Chen, Runjian, Liang, Zhixuan, Hu, Mengkang, Tao, Chaofan, Sun, Peize, Yu, Haibao, Yang, Chao, Shao, Wenqi, Wang, Wenhai, Dai, Jifeng, Qiao, Yu, Ding, Mingyu, Luo, Ping
Robotic behavior synthesis, the problem of understanding multimodal inputs and generating precise physical control for robots, is an important part of Embodied AI. Despite successes in applying multimodal large language models for high-level understa
Externí odkaz:
http://arxiv.org/abs/2402.16117
Autor:
Chen, Junting, Mu, Yao, Yu, Qiaojun, Wei, Tianming, Wu, Silang, Yuan, Zhecheng, Liang, Zhixuan, Yang, Chao, Zhang, Kaipeng, Shao, Wenqi, Qiao, Yu, Xu, Huazhe, Ding, Mingyu, Luo, Ping
Rapid progress in high-level task planning and code generation for open-world robot manipulation has been witnessed in Embodied AI. However, previous studies put much effort into general common sense reasoning and task planning capabilities of large-
Externí odkaz:
http://arxiv.org/abs/2402.14623
In the realm of household robotics, the Zero-Shot Object Navigation (ZSON) task empowers agents to adeptly traverse unfamiliar environments and locate objects from novel categories without prior explicit training. This paper introduces VoroNav, a nov
Externí odkaz:
http://arxiv.org/abs/2401.02695
Diffusion models have demonstrated strong potential for robotic trajectory planning. However, generating coherent trajectories from high-level instructions remains challenging, especially for long-range composition tasks requiring multiple sequential
Externí odkaz:
http://arxiv.org/abs/2312.11598