What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Computer vision
Robert Mahony mainly investigates Control theory, Control engineering, Artificial intelligence, Robotics and Backstepping.
As part of the same scientific family, Robert Mahony usually focuses on Control theory, concentrating on Visual servoing and intersecting with Kinematics.
His Control engineering study also includes
- Robot that intertwine with fields like Rotor and Control theory,
- Control that intertwine with fields like Lyapunov redesign.
As a part of the same scientific family, Robert Mahony mostly works in the field of Artificial intelligence, focusing on Computer vision and, on occasion, Robust control.
His Backstepping study combines topics in areas such as Body force and Motion control.
His work in Control-Lyapunov function addresses issues such as Mathematical optimization, which are connected to fields such as Differential geometry, Eigenvalues and eigenvectors and Numerical linear algebra.
His most cited work include:
- Optimization Algorithms on Matrix Manifolds (2039 citations)
- Nonlinear Complementary Filters on the Special Orthogonal Group (1089 citations)
- Multirotor Aerial Vehicles: Modeling, Estimation, and Control of Quadrotor (814 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Control theory, Artificial intelligence, Computer vision, Control engineering and Robot.
His research on Control theory frequently connects to adjacent areas such as Position.
His studies link Kinematics with Artificial intelligence.
In his study, Rotor is strongly linked to Aerodynamics, which falls under the umbrella field of Control engineering.
Robert Mahony has researched Robot in several fields, including Simulation and Haptic technology.
His Servo control research includes elements of Control system, Exponential stability and Adaptive control.
He most often published in these fields:
- Control theory (46.69%)
- Artificial intelligence (33.07%)
- Computer vision (21.40%)
What were the highlights of his more recent work (between 2014-2020)?
- Control theory (46.69%)
- Artificial intelligence (33.07%)
- Observer (10.12%)
In recent papers he was focusing on the following fields of study:
Robert Mahony focuses on Control theory, Artificial intelligence, Observer, Computer vision and Kinematics.
A large part of his Control theory studies is devoted to Trajectory.
In the field of Artificial intelligence, his study on Robot and Robotics overlaps with subjects such as Homography.
His Robot research incorporates elements of Control engineering and Haptic technology.
His research integrates issues of Rotation, Exponential stability, Rotation matrix, Velocity measurement and Position in his study of Observer.
Robert Mahony has included themes like Gyroscope and Specular reflection in his Computer vision study.
Between 2014 and 2020, his most popular works were:
- Observers for invariant systems on Lie groups with biased input measurements and homogeneous outputs (36 citations)
- A geometric nonlinear observer for simultaneous localisation and mapping (29 citations)
- Thrust Control for Multirotor Aerial Vehicles (27 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Computer vision
Robert Mahony mainly focuses on Control theory, Observer, Observer, Lie group and Pose.
The study incorporates disciplines such as Aerodynamics, Thrust and Rotor in addition to Control theory.
Within one scientific family, Robert Mahony focuses on topics pertaining to Quotient under Observer, and may sometimes address concerns connected to Robot.
Computer vision and Artificial intelligence are inherently bound to his Observer studies.
His study explores the link between Lie group and topics such as Homogeneous space that cross with problems in Algorithm, Rigid body and Matrix representation.
Robert Mahony focuses mostly in the field of Pose, narrowing it down to matters related to State observer and, in some cases, Position, Inertial frame of reference and Robustness.
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