Zobrazeno 1 - 10
of 164
pro vyhledávání: '"Lin MingJie"'
Dexterous manipulation, particularly adept coordinating and grasping, constitutes a fundamental and indispensable capability for robots, facilitating the emulation of human-like behaviors. Integrating this capability into robots empowers them to supp
Externí odkaz:
http://arxiv.org/abs/2404.02284
Autor:
Alhussain, Azzam, Lin, Mingjie
Accelerating Human Action Recognition (HAR) efficiently for real-time surveillance and robotic systems on edge chips remains a challenging research field, given its high computational and memory requirements. This paper proposed an integrated end-to-
Externí odkaz:
http://arxiv.org/abs/2311.03390
Reactive trajectory optimization for robotics presents formidable challenges, demanding the rapid generation of purposeful robot motion in complex and swiftly changing dynamic environments. While much existing research predominantly addresses robotic
Externí odkaz:
http://arxiv.org/abs/2310.01738
Real-time interception of fast-moving objects by robotic arms in dynamic environments poses a formidable challenge due to the need for rapid reaction times, often within milliseconds, amidst dynamic obstacles. This paper introduces a unified control
Externí odkaz:
http://arxiv.org/abs/2209.13628
Autor:
Alhussain, Azzam, Lin, Mingjie
Acceleration of Convolutional Neural Network (CNN) on edge devices has recently achieved a remarkable performance in image classification and object detection applications. This paper proposes an efficient and scalable CNN-based SoC-FPGA accelerator
Externí odkaz:
http://arxiv.org/abs/2207.10723
Merkle tree is a widely used tree structure for authentication of data/metadata in a secure computing system. Recent state-of-the art secure systems use a smaller-sized MT, namely Bonsai Merkle Tree (BMT) to protect the metadata such as encryption co
Externí odkaz:
http://arxiv.org/abs/2204.08976
Autor:
Dastider, Apan, Lin, Mingjie
Safe and efficient collaboration among multiple robots in unstructured environments is increasingly critical in the era of Industry 4.0. However, achieving robust and autonomous collaboration among humans and other robots requires modern robotic syst
Externí odkaz:
http://arxiv.org/abs/2203.13821
Autor:
Dastider, Apan, Lin, Mingjie
In modern robotics, effectively computing optimal control policies under dynamically varying environments poses substantial challenges to the off-the-shelf parametric policy gradient methods, such as the Deep Deterministic Policy Gradient (DDPG) and
Externí odkaz:
http://arxiv.org/abs/2203.14905
Autor:
Dastider, Apan, Lin, Mingjie
DAMON leverages manifold learning and variational autoencoding to achieve obstacle avoidance, allowing for motion planning through adaptive graph traversal in a pre-learned low-dimensional hierarchically-structured manifold graph that captures intric
Externí odkaz:
http://arxiv.org/abs/2203.13282
Autor:
Luo, Jinchen, Lin, Mingjie, Chen, Minyu, Chen, Jinwei, Zhou, Xinwei, Liu, Kezhi, Liang, Yanping, Chen, Jiajie, Liang, Hui, Wang, Zhu, Deng, Qiong, Wang, Jieyan, Jin, Meiyu, Luo, Junhang, Chen, Wei, Cen, Junjie
Publikováno v:
In Translational Oncology January 2025 51
