What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Control theory
John L. Crassidis mainly focuses on Control theory, Extended Kalman filter, Kalman filter, Attitude control and Spacecraft.
His Quaternion study in the realm of Control theory interacts with subjects such as Gaussian process.
John L. Crassidis focuses mostly in the field of Extended Kalman filter, narrowing it down to matters related to Linear least squares and, in some cases, Recursive least squares filter.
His Kalman filter research is multidisciplinary, relying on both Inertial navigation system, Sliding mode control, Magnetorquer, Reaction wheel and Noise.
His Spacecraft study combines topics from a wide range of disciplines, such as Kinematics, Variable structure control, Euler equations, Control engineering and Angular velocity.
His Invariant extended Kalman filter research is multidisciplinary, incorporating elements of Alpha beta filter, Ensemble Kalman filter and Fast Kalman filter.
His most cited work include:
- Survey of nonlinear attitude estimation methods (854 citations)
- Optimal Estimation of Dynamic Systems (758 citations)
- Unscented Filtering for Spacecraft Attitude Estimation (721 citations)
What are the main themes of his work throughout his whole career to date?
John L. Crassidis spends much of his time researching Control theory, Kalman filter, Extended Kalman filter, Spacecraft and Algorithm.
His Control theory research incorporates elements of Covariance, Attitude determination and Errors-in-variables models.
His studies in Kalman filter integrate themes in fields like Inertial navigation system and Computer vision.
John L. Crassidis has researched Extended Kalman filter in several fields, including Filter, Estimator, Filter, Noise and Inertial measurement unit.
His Spacecraft research is multidisciplinary, incorporating perspectives in Control engineering, Attitude control, Torque, Angular velocity and Star.
Within one scientific family, John L. Crassidis focuses on topics pertaining to Mathematical optimization under Algorithm, and may sometimes address concerns connected to Applied mathematics.
He most often published in these fields:
- Control theory (42.21%)
- Kalman filter (22.05%)
- Extended Kalman filter (17.49%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (11.79%)
- Computer vision (9.51%)
- Total least squares (3.04%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Computer vision, Total least squares, Attitude determination and Spacecraft.
The study incorporates disciplines such as Pattern recognition, Star, Situation awareness and Identification in addition to Artificial intelligence.
His Computer vision research integrates issues from Frame, Inertial navigation system, Acceleration and Filter.
His work is dedicated to discovering how Attitude determination, Control are connected with Control theory and other disciplines.
His study in Control theory focuses on Linear system in particular.
John L. Crassidis interconnects Electrical engineering, Ultra-wideband, Orbit determination, Range and Line-of-sight in the investigation of issues within Spacecraft.
Between 2017 and 2021, his most popular works were:
- Output-Redefinition-Based Dynamic Inversion Control for a Nonminimum Phase Hypersonic Vehicle (24 citations)
- Hip and Trunk Kinematics Estimation in Gait Through Kalman Filter Using IMU Data at the Ankle (17 citations)
- Space-object shape inversion via adaptive hamiltonian Markov Chain Monte Carlo (6 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Control theory
Artificial intelligence, Total least squares, Computer vision, Statistics and Space object are his primary areas of study.
His studies deal with areas such as Ranking, Machine learning and Situation awareness as well as Artificial intelligence.
His work deals with themes such as Frame, Inertial navigation system, Star and Pattern recognition, which intersect with Computer vision.
The various areas that he examines in his Statistics study include Gaussian noise and Attitude determination.
His research integrates issues of Characterization, Estimator, Orbit and Optics in his study of Space object.
As a part of the same scientific family, John L. Crassidis mostly works in the field of Geodesy, focusing on Calibration and, on occasion, Identification, Spacecraft, Focal length, Invariant and Camera resectioning.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
