Fibonacci sequence, golden section, Kalman filter and optimal control A. Benavoli1, L. Chisci2 and A. Farina3 1

Source URL: people.idsia.ch

LQG-Based Planning, Sensing, and Control of Steerable Needles Jur van den Berg1 , Sachin Patil1 , Ron Alterovitz1, Pieter Abbeel2 , Ken Goldberg2 Abstract This paper presents a technique for planning and controlling beve

Source URL: goldberg.berkeley.edu

• Control theory
• Statistics
• Systems theory
• Systems science
• Kalman filter
• LinearquadraticGaussian control
• State observer
• Normal distribution
• State-space representation
• Optimal control

Gaussian Belief Space Planning with Discontinuities in Sensing Domains Sachin Patil, Yan Duan, John Schulman, Ken Goldberg, Pieter Abbeel Abstract— Discontinuities in sensing domains are common when planning for many r

Source URL: goldberg.berkeley.edu

• Robot control
• Control theory
• Kalman filter
• Motion planning
• Partially observable Markov decision process
• Robotics
• Distribution
• Trajectory optimization

An EM-Algorithm for Maximum Likelihood Estimation of Vector Autoregressions with Mixed Frequency Data J¨urgen Antony∗ and Torben Klarl† February 13, 2016 Abstract

Source URL: www.wiwi.uni-augsburg.de

• Statistics
• Estimation theory
• Statistical inference
• Robot control
• Kalman filter
• Maximum likelihood estimation
• Expectationmaximization algorithm
• Exponential family
• Principal component analysis
• Confidence interval
• Draft:Pirate programming

C:/Users/Jur van den Berg/Documents/papers/ICRA10 - Surgical Learning/vandenBergDuckworthMillerHuWanFuGoldbergAbbeel-icra10.dvi

Source URL: goldberg.berkeley.edu

• Physics
• Mechanics
• Mechanical engineering
• Ballistics
• Engineering
• Robot control
• Trajectory
• Kinematics
• Kalman filter
• Robotics
• Dynamical system
• Work

Gaussian Belief Space Planning for Imprecise Articulated Robots Alex Lee Sachin Patil John Schulman Zoe McCarthy Jur van den Berg Ken Goldberg Pieter Abbeel Abstract— For many emerging applications, actuators are being

Source URL: goldberg.berkeley.edu

• Statistics
• Mathematical analysis
• Probability
• Robot control
• Mathematical optimization
• Dynamic programming
• Stochastic control
• Partially observable Markov decision process
• Trajectory optimization
• Kalman filter
• Motion planning
• Normal distribution

Image interpolation and denoising for division of focal plane sensors using Gaussian Processes Elad Gilboa,1 John P. Cunningham,2 Arye Nehorai,1 and Viktor Gruev 3 1 Preston

Source URL: stat.columbia.edu

• Multivariate interpolation
• Image processing
• Interpolation
• Gaussian process
• Bicubic interpolation
• Polarization
• Regression analysis
• Kalman filter
• Normal distribution
• Kriging

Adaptive Collective Routing Using Gaussian Process Dynamic Congestion Models Siyuan Liu, Yisong Yue, Ramayya Krishnan Carnegie Mellon University {siyuan,yisongyue,rk2x}@cmu.edu

Source URL: select.cs.cmu.edu

• Statistics
• Probability theory
• Algebra of random variables
• Covariance and correlation
• Routing
• Covariance
• Shortest path problem
• Mathematics
• Multivariate statistics
• Kalman filter

J Intell Robot Syst:287–299 DOIs10846z Fusion of IMU and Vision for Absolute Scale Estimation in Monocular SLAM Gabriel Nützi · Stephan Weiss ·

Source URL: rpg.ifi.uzh.ch

• Robot control
• Control theory
• Telecommunications engineering
• Estimation theory
• Electrical engineering
• Linear filters
• Kalman filter
• Inertial measurement unit
• Simultaneous localization and mapping
• Sensor fusion
• Spline
• Frame of reference

Towards Evasive Maneuvers with Quadrotors using Dynamic Vision Sensors Elias Mueggler, Nathan Baumli, Flavio Fontana and Davide Scaramuzza Robotics and Perception Group, University of Zurich, Switzerland

Source URL: rpg.ifi.uzh.ch

• Robot control
• Control theory
• Kalman filter
• Quadcopter
• Optical flow
• Music tracker