GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
J Ko, D Fox�- Autonomous Robots, 2009 - Springer
Bayesian filtering is a general framework for recursively estimating the state of a dynamical
system. Key components of each Bayes filter are probabilistic prediction and observation …
system. Key components of each Bayes filter are probabilistic prediction and observation …
Mechanisms of the anatomically correct testbed hand
…, Z Xu, MJV Weghe, BH Brown, J Ko…�- IEEE/ASME�…, 2011 - ieeexplore.ieee.org
We have built an anatomically correct testbed (ACT) hand with the purpose of understanding
the intrinsic biomechanical and control features in human hands that are critical for …
the intrinsic biomechanical and control features in human hands that are critical for …
Learning GP-BayesFilters via Gaussian process latent variable models
J Ko, D Fox�- Autonomous Robots, 2011 - Springer
GP-BayesFilters are a general framework for integrating Gaussian process prediction and
observation models into Bayesian filtering techniques, including particle filters and extended …
observation models into Bayesian filtering techniques, including particle filters and extended …
Gaussian processes and reinforcement learning for identification and control of an autonomous blimp
Blimps are a promising platform for aerial robotics and have been studied extensively for this
purpose. Unlike other aerial vehicles, blimps are relatively safe and also possess the ability …
purpose. Unlike other aerial vehicles, blimps are relatively safe and also possess the ability …
Distributed multirobot exploration and mapping
D Fox, J Ko, K Konolige, B Limketkai…�- Proceedings of the�…, 2006 - ieeexplore.ieee.org
Efficient exploration of unknown environments is a fundamental problem in mobile robotics.
We present an approach to distributed multirobot mapping and exploration. Our system …
We present an approach to distributed multirobot mapping and exploration. Our system …
GP-UKF: Unscented Kalman filters with Gaussian process prediction and observation models
This paper considers the use of non-parametric system models for sequential state estimation.
In particular, motion and observation models are learned from training examples using …
In particular, motion and observation models are learned from training examples using …
A practical, decision-theoretic approach to multi-robot mapping and exploration
An important assumption underlying virtually all approaches to multi-robot exploration is prior
knowledge about their relative locations. This is due to the fact that robots need to merge …
knowledge about their relative locations. This is due to the fact that robots need to merge …
Bioresorbable pressure sensors protected with thermally grown silicon dioxide for the monitoring of chronic diseases and healing processes
Pressures in the intracranial, intraocular and intravascular spaces are clinically useful for
the diagnosis and management of traumatic brain injury, glaucoma and hypertension, …
the diagnosis and management of traumatic brain injury, glaucoma and hypertension, …
Map merging for distributed robot navigation
K Konolige, D Fox, B Limketkai, J Ko…�- …�2003 IEEE/RSJ�…, 2003 - ieeexplore.ieee.org
A set of robots mapping an area can potentially combine their information to produce a
distributed map more efficiently than a single robot alone. We describe a general framework for …
distributed map more efficiently than a single robot alone. We describe a general framework for …
Transport, phase reactions, and hysteresis of iron fluoride and oxyfluoride conversion electrode materials for lithium batteries
JK Ko, KM Wiaderek, N Pereira…�- …�applied materials &�…, 2014 - ACS Publications
Potentiostatic intermittent titration technique (PITT) was applied to FeF 2 , FeF 3 , and FeO
0.67 F 1.33 to gain insight into the transport-related aspects of the conversion reaction by …
0.67 F 1.33 to gain insight into the transport-related aspects of the conversion reaction by …