Contact State Estimation Using Multiple Model Estimation and Hidden Markov Models
نویسندگان
چکیده
منابع مشابه
Contact State Estimation using Multiple Model Estimation and Hidden Markov Models
This paper presents an approach to estimating the contact state between a robot and its environment during task execution. Contact states are modeled by constraint equations parameterized by time-dependent sensor data and timeindependent object properties. At each sampling time, multiple model estimation is used to assess the most likely contact state. The assessment is performed by a Hidden Ma...
متن کاملHidden Markov models using fuzzy estimation
In the conventional hidden Markov model, the model parameters are reestimated by an iterative procedure known as the Baum-Welch method. This paper proposes an alternative procedure using fuzzy estimation, which is generalised from the fuzzy c-means and the BaumWelch methods. An extension of this approach, which uses a garbage state to deal with outlier data is also proposed. Experiments using t...
متن کاملKey Estimation Using a Hidden Markov Model
A novel technique to estimate the predominant key in a musical excerpt is proposed. The key space is modelled by a 24-state Hidden Markov Model (HMM), where each state represents one of the 24 major and minor keys, and each observation represents a chord transition, or pair of consecutive chords. The use of chord transitions as the observations models a greater temporal dependency between conse...
متن کاملThree techniques for state order estimation of hidden Markov models
In this contribution three examples of techniques that can be used for state order estimation of hidden Markov models are given. The methods are also exem-pliied using real laser range data, and the computational burden of the three methods is discussed. Two techniques, Maximum Description Length and Maximum a Posteriori Estimate, are shown to be very similar under certain circumstances. The th...
متن کاملBlind channel estimation and data detection using hidden Markov models
In this correspondence, we propose applying the hidden Markov models (HMM) theory to the problem of blind channel estimation and data detection. The Baum–Welch (BW) algorithm, which is able to estimate all the parameters of the model, is enriched by introducing some linear constraints emerging from a linear FIR hypothesis on the channel. Additionally, a version of the algorithm that is suitable...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The International Journal of Robotics Research
سال: 2004
ISSN: 0278-3649,1741-3176
DOI: 10.1177/0278364904042195