Results 41 to 50 of about 131,091 (318)

Recent Advances of Slip Sensors for Smart Robotics

Advanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang, Liao Wu, Shuai He, Zhao Sha, Yuwan Huang, Shuying Wu, Dewei Chu, Chun H. Wang, Shuhua Peng   +8 more
wiley   +1 more source

Comparison of Semi-Markov and Markov Processes

The Annals of Mathematical Statistics, 1971
Conditions are given under which a semi-Markov process $Z(t)$ can be obtained from a Markov process $Y(t)$ by a time change (i.e. $Z(t) = Y(\gamma(t))$). Estimates are given for $P\{\sup_{s\leqq t} |s - \gamma(s)| > \varepsilon\}$ and the construction is used to give conditions under which a sequence of semi-Markov processes will have the same ...
openaire   +2 more sources

Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space

Advanced Robotics Research, EarlyView.
A quadruped robot masters dynamic jumps through constrained spaces with animal‐inspired moves and intelligent vision control. This hierarchical learning approach combines imitation of biological agility with real‐time trajectory planning. Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating ...
Zeren Luo, Jiahui Zhang, Yimin Han, Ji Ma, Minghao Lu, Ioannis Havoutis, Peng Lu   +6 more
wiley   +1 more source

Controllable Summarization with Constrained Markov Decision Process

Transactions of the Association for Computational Linguistics, 2021
We study controllable text summarization, which allows users to gain control on a particular attribute (e.g., length limit) of the generated summaries. In this work, we propose a novel training framework based on Constrained Markov Decision Process (CMDP)
Hou Pong Chan, Lu Wang, Irwin King
doaj   +1 more source

Stable Imitation of Multigait and Bipedal Motions for Quadrupedal Robots Over Uneven Terrains

Advanced Robotics Research, EarlyView.
How are quadrupedal robots empowered to execute complex navigation tasks, including multigait and bipedal motions? Challenges in stability and real‐world adaptation persist, especially with uneven terrains and disturbances. This article presents an imitation learning framework that enhances adaptability and robustness by incorporating long short‐term ...
Erdong Xiao, Yinzhao Dong, Ji Ma, Peng Lu   +3 more
wiley   +1 more source

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

Advanced Robotics Research, EarlyView.
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek, Herman van der Kooij, Douwe Dresscher, Mark Vlutters   +3 more
wiley   +1 more source

Features of using Markov decision-making processes when modeling attacks on artificial intelligence systems

Вестник Самарского университета: Естественнонаучная серия
In this paper, we study the features of modeling attacks on artificial intelligence systems. Markov decision-making processes are used in the construction of the model.
Igor A. Vetrov, Vladislav V. Podtopelny
doaj   +1 more source

Vacation Policy for k-out-of-n Redundant System with Reboot Delay [PDF]

International Journal of Mathematical, Engineering and Management Sciences
Redundancy is a well-known concept for system resilience; k-out-of-n redundancy stipulates that a minimum number of functional components must be present for the system to function.
Vaishali Tyagi, Mangey Ram, Monika Manglik, Ritu Arora   +3 more
doaj   +1 more source

Robotic Control for Human–Robot Collaborative Assembly Based on Digital Human Model and Reinforcement Learning

Advanced Robotics Research, EarlyView.
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao, Hongzhou Ai, Wenjun Xu, Zude Zhou, Lihui Wang   +4 more
wiley   +1 more source

RELIABILITY ANALYSIS OF COMPUTER NETWORKS USING PARAMETRIC FAILURE CRITERIA

Статистика и экономика, 2016
A mathematical model, which allows to obtain expressions for the determination of parameters of reliability of computer ne t w o rks co n sis t i n g o f i den t i c al recoverable elements.
Oleg A. Tkachev
doaj   +1 more source