Index

  • a

  • AR. see augmented reality (AR)
  • assembly‐plan‐from‐observation (APO) method
  • augmented reality (AR)
  • automated guided vehicles (AGVs)
  • automatic programming systems

  • b

  • backward algorithm
  • Bakis left‐right topology
  • Baum–Welch
    • algorithm
    • parameter estimation formulas
  • Bayesian belief networks
  • Bayesian information criterion
  • Bayes theorem
  • BFGS. see Broyden–Fletcher–Goldfarb–Shanno (BFGS)
  • boundary conditions
  • Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm

  • c

  • camera calibration errors
  • camera modeling errors
  • canonical variable
  • Cartesian pose
  • Cartesian space
    • constraints
  • clique
  • close‐range photogrammetric techniques
  • clustering techniques
  • compliant motions
  • conditional random fields (CRFs)
    • clique
    • forward–backward algorithm
    • linear chain
    • maximal cliques
    • training and inference
  • constraints
    • Cartesian space
    • image‐space
    • robot manipulator
    • vision sensor
  • controller‐specific programming language
  • convex optimization
    • problem
  • covariance function
  • covariance matrix
    • Cartesian trajectories
    • eigenvectors of
  • CRFs. see conditional random fields (CRFs)
  • curve smoothing techniques

  • d

  • damped least squares method
  • data acquisition system
  • data points
  • data preprocessing techniques
  • data scaling
  • dataset
  • Denavit–Hartenberg convention
  • DMPs. see dynamic motion primitives (DMPs)
  • dot tracker method
  • dynamical systems approach
  • dynamic motion primitives (DMPs)
    • approach
  • dynamic time warping (DTW)
    • algorithm
    • scaling

  • e

  • electromyography (EMG) signals
  • end‐effector
  • Euclidean distance
  • Euclidean norm
  • Euler’s forward discretization scheme
  • Euler’s roll–pitch–yaw angles
  • expectation maximization (EM) algorithm
  • exploration based systems
  • extended focused assessment with sonography in trauma (eFAST)
  • extrinsic camera parameters

  • f

  • field of view (FoV)
  • focal length
    • scaling factors
  • forward algorithm
  • forward differential kinematics
  • FoV. see field of view (FoV)
  • fuzzy logic

  • g

  • Gaussian distribution
  • Gaussian mixture model (GMM)
    • approach
  • Gaussian mixture regression (GMR)
  • Gaussian probability density functions
  • Gaussian process regression (GPR)
    • covariance function/kernel
    • Gaussian process model
    • zero‐mean Gaussian distribution
  • GMM. see Gaussian mixture model (GMM)
  • GPR. see Gaussian process regression (GPR)

  • h

  • hidden Markov model (HMM)
    • continuous observation data
    • decoding problem
    • evaluation problem
    • modeling and generalization
      • codebook formation
      • initialization
      • training and trajectory segmentation
    • stochastic process
    • training model
  • high‐level multipurpose language
  • HMM. see hidden Markov model (HMM)
  • homography matrix
  • horizontal pixel coordinates
  • humanoid robots
  • human–robot interaction (HRI)
    • PbD
  • HVS. see hybrid visual servoing (HVS)
  • hybrid visual servoing (HVS)

  • i

  • image‐based task planning
    • constraints
    • learning environment
    • objective function
    • optimization model
    • second‐order conic optimization
    • task planning
  • image‐based visual servoing (IBVS)
    • approach
    • steady‐state errors of
    • tracking control
  • image Jacobian matrix
  • image noise
  • image processing algorithms
  • image‐space constraints
  • industrial robots
    • assembly
    • surface finishing
  • infrared optical markers
  • interaction matrix
  • intrinsic camera parameters
    • convex optimization
    • GMM/GMR and DMPs approach
  • inverse differential kinematics algorithm
  • inverse kinematics
    • controller
    • problem
  • iterative image‐based learning schemes

  • j

  • Jacobian matrix

  • k

  • Kalman filter estimation
  • Kalman smoothing algorithm
  • kernel regression
  • knowledge transfer

  • l

  • LBG algorithm. see Linde–Buzo–Gray (LBG) algorithm
  • learning algorithms
  • learning by demonstration (LbD)
  • learning from demonstration (LfD)
  • learning systems. see automatic programming systems
  • least‐square
    • estimation scheme
    • methods
  • Linde–Buzo–Gray (LBG) algorithm
  • linear constraints
  • linear scaling
    • approaches
    • technique
  • locally weighted regression
    • Euclidean distance
    • kernel functions
    • kernel regression
    • Minkowski distance function
    • nearest‐neighbor approach
    • nonlinear force function
    • query point

  • m

  • machine vision
  • magnetic sensors
  • Mahalanobis distance
  • manual programming systems
  • mass–damper–spring system
  • MATLAB
    • CRF chain toolbox
  • MATLAB executable (MEX) file
  • maximal cliques
  • measurement noise
  • medical robots
  • Minkowski distance function
  • mixed reality (MR)
  • modeling errors
  • monotonicity condition
  • motion primitives, hierarchy of

  • n

  • neural networks
  • noise variance
  • nonuniform rational B‐splines (NURBS)
  • null key points

  • o

  • observation‐based systems
  • off‐line programming (OLP)
  • open‐loop kinematic chain
  • optical marker‐based sensors
  • optical tracker
  • optimization algorithms
  • Optotrak Certus

  • q

  • quadratic weighting function
  • QuaRC
    • IBVS tracking
    • open architecture system
    • toolbox
  • quasi‐Newton methods
  • query point

  • r

  • radial basis function
  • random noise variable
  • reference coordinate system
  • regression techniques
  • RMS. see root‐mean‐square (RMS)
  • robot
    • compliance planning
    • control techniques
    • end‐point frame
    • environment interactions
    • grasp planning application
    • gripper
    • inverse kinematics. see end‐effector
    • Jacobian matrix
      • pseudoinverse of
    • kinematic constraints
    • kinematic singularities
    • manipulator constraints
    • modeling errors
    • motion
      • accuracy
      • planning
      • real‐time control of
    • PbD
      • neural networks
      • overview of
      • statistical models
      • teaching/learning process
      • VR
    • programming methods
    • sensory data
  • robust image‐based tracking control
    • closed‐architecture system
    • dot tracker method
    • experiments
    • image Jacobian matrix, pseudoinverse of
    • MATLAB
    • optimization model
    • PID controllers
    • robustness analysis
    • simulations
  • robust learning
    • demonstrated motions, encoding of
    • PbD plans, reproduction of
  • root‐mean‐square (RMS)
    • deviations
    • errors

  • s

  • second‐order conic optimization model
  • sensor fusion
  • sensors noise
  • service robots
  • Silhouette coefficient
  • Simulink
  • skew‐symmetric matrix
  • skill transfer
  • slack variables
  • social robots
  • spatial task constraints
  • spline regression
    • cluster model
    • CRF modeling and generalization
      • functions formation
      • trajectories encoding and generalization
    • curve‐fitting techniques
    • data points
    • data processing
    • Euler roll–pitch–yaw angles
    • forward algorithm
    • Fourier transform
    • Gaussian covariances
    • GMM/GMR
    • key points, extraction of
    • LBG algorithm
    • modeling and generalization
      • comparison with related work
      • key points weighting
      • spline fitting and interpolation
      • temporal normalization, DTW
    • null key points
    • PbD techniques
    • query point
    • RMS error
    • standard deviation
    • support vector machine (SVM) algorithm
    • vector quantization
    • Viterbi algorithm
    • weighting coefficients
  • Stanford Research Institute Problem Solver (STRIPS)
  • stereo cameras
  • support vector machine (SVM) algorithm
  • system architecture, PbD
    • learning interfaces
    • program generation and task execution
    • task analysis and planning
    • task representation and modeling

  • t

  • task execution
    • image‐based task planning
    • kinematic robot control
    • robust image‐based tracking control
    • vision‐based trajectory tracking control
  • task modeling
    • CRF
    • DMP
    • GMM
    • HMM
  • task perception
    • optical tracking systems
    • vision cameras
  • task planning
    • CRFs
    • GMR
    • GPR
    • locally weighted regression
    • spline regression
  • task representation
    • abstraction level
    • Cartesian space
    • data acquisition system
    • data scaling and aligning
    • dynamic programming technique
    • PbD
    • probabilistic learning
  • teleoperation
  • third order spline regression
  • three‐dimensional (3D) simulators
  • trajectory learning
    • skill acquisition
    • task planning

  • v

  • vector quantization
  • vertical pixel coordinates
  • vertical spatial image
  • virtual reality (VR)
  • virtual robot
  • vision‐based trajectory tracking control
    • advanced visual servoing methods
    • IBVS
    • PBVS
  • vision cameras
    • Cartesian space
    • FoV
    • look‐and‐move control
    • pixels resolution
  • vision sensor constraints
  • visual servoing. see also image Jacobian matrix; interaction matrix
    • control
    • methods
  • Viterbi algorithm
  • von Mises basis functions
  • VR–AR techniques

  • w

  • weighted least‐norm method
  • weighting coefficients
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