Results 51 to 60 of about 14,908,682 (295)

Analysis of multimodal Bayesian nonparametric autoregressive hidden Markov models for process monitoring in robotic contact tasks

International Journal of Advanced Robotic Systems, 2019
Robot introspection aids robots to understand what they do and how they do it. Previous robot introspection techniques have often used parametric hidden Markov models or supervised learning techniques, implying that the number of hidden states or classes
Hongmin Wu, Yisheng Guan, Juan Rojas
doaj   +1 more source

Real-Time Assembly Support System with Hidden Markov Model and Hybrid Extensions

Mathematics, 2022
This paper presents a context-aware adaptive assembly assistance system meant to support factory workers by embedding predictive capabilities. The research is focused on the predictor which suggests the next assembly step.
Arpad Gellert, Stefan-Alexandru Precup, Alexandru Matei, Bogdan-Constantin Pirvu, Constantin-Bala Zamfirescu   +4 more
doaj   +1 more source

Duration modeling with hidden Markov models [PDF]

The Journal of the Acoustical Society of America, 1993
In hidden Markov modeling (HMM) of speech signals, the statistics of speech characteristics are represented by HMM parameters after the HMM training. This procedure is purely statistical. This study concerns the incorporation of explicit knowledge into the HMM training. Therefore one specific parameter, i.e., segment duration, was selected. In order to
ten Bosch, L.F.M., Wang, X., Pols, L.C.W.   +2 more
openaire   +2 more sources

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

Mutual Adaptation and Influence: Review of Latent Dynamics Models in Human–Robot Interaction

Advanced Robotics Research, EarlyView.
Robots are becoming better teammates by learning hidden patterns in how people act. This review covers how state‐of‐the‐art approaches leverage these patterns to help robots not only react but also anticipate and guide cooperation. Here, we synthesize a unifying framework for these approaches, classify and review existing works, and highlight key ...
Mason O. Smith, Sunny Amatya, Seyed Yousef Soltanian, Jonathan Bush, Wenlong Zhang   +4 more
wiley   +1 more source

Feedforward Factorial Hidden Markov Model

Mathematics
This paper introduces a novel kind of factorial hidden Markov model (FHMM), specifically the feedforward FHMM (FFHMM). In contrast to traditional FHMMs, the FFHMM is capable of directly utilizing supplementary information from observations through ...
Zhongxing Peng, Wei Huang, Yinghui Zhu
doaj   +1 more source

Hidden Markov Model for Stock Trading

International Journal of Financial Studies, 2018
Hidden Markov model (HMM) is a statistical signal prediction model, which has been widely used to predict economic regimes and stock prices. In this paper, we introduce the application of HMM in trading stocks (with S&P 500 index being an example ...
Nguyet Nguyen
doaj   +1 more source

Hidden Markov Model Cryptanalysis [PDF]

, 2003
We present HMM attacks, a new type of cryptanalysis based on modeling randomized side channel countermeasures as Hidden Markov Models (HMM’s). We also introduce Input Driven Hidden Markov Models (IDHMM’s), a generalization of HMM’s that provides a powerful and unified cryptanalytic framework for analyzing countermeasures whose operational behavior can ...
Chris Karlof, David A. Wagner 0001
openaire   +1 more source

Push the Limits: Human‐Like Multimodal Extreme Embodied Intelligence for Autonomous Racing

Advanced Robotics Research, EarlyView.
Autonomous racing tests embodied intelligence under extreme control limits of speed, actuation, and decision‐making. Inspired by human multimodality, we present Apex, an embodied agent deployed on a super‐formula racing car at Yas Marina. Integrating physics‐informed perception, multimodal learning, and tasking, Apex cuts lap times by 15% and achieves ...
Yanxin Zhou, Baichuan Lou, Wenhui Huang, Binbin Hu, Haohan Yang, Haochen Liu, Xiangkun He, Chee Kiong Ong, Yiran Zhang, Tianchu Su, Bolin Zhao, Xiaoyu Mo, Holden King Ho Li, Chen Lv   +13 more
wiley   +1 more source

Hidden Markov Model for Stock Selection

Risks, 2015
The hidden Markov model (HMM) is typically used to predict the hidden regimes of observation data. Therefore, this model finds applications in many different areas, such as speech recognition systems, computational molecular biology and financial market ...
Nguyet Nguyen, Dung Nguyen
doaj   +1 more source