What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Mathematical analysis
Panagiotis Tsiotras spends much of his time researching Control theory, Attitude control, Spacecraft, Mathematical optimization and Vehicle dynamics.
His research links Kinematics with Control theory.
The concepts of his Kinematics study are interwoven with issues in Plane and Rigid body.
His Spacecraft study integrates concerns from other disciplines, such as Actuator and Rotational symmetry.
His Mathematical optimization research incorporates elements of Algorithm, Controllability, Partition and Motion planning.
Panagiotis Tsiotras combines subjects such as Slip, Simulation and Throttle with his study of Vehicle dynamics.
His most cited work include:
- Stabilization and optimality results for the attitude control problem (277 citations)
- DYNAMIC FRICTION MODELS FOR ROAD/TIRE LONGITUDINAL INTERACTION (273 citations)
- Leader–follower cooperative attitude control of multiple rigid bodies (267 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Control theory, Mathematical optimization, Optimal control, Motion planning and Spacecraft.
His studies deal with areas such as Kinematics and Rigid body as well as Control theory.
Within one scientific family, Panagiotis Tsiotras focuses on topics pertaining to Path under Mathematical optimization, and may sometimes address concerns connected to Curvature.
In Optimal control, Panagiotis Tsiotras works on issues like Nonlinear system, which are connected to Bellman equation, Stochastic differential equation and Stochastic control.
The study incorporates disciplines such as Graph, Theoretical computer science and Vehicle dynamics in addition to Motion planning.
His research integrates issues of Dual quaternion and Actuator in his study of Spacecraft.
He most often published in these fields:
- Control theory (41.99%)
- Mathematical optimization (24.93%)
- Optimal control (14.96%)
What were the highlights of his more recent work (between 2017-2021)?
- Mathematical optimization (24.93%)
- Control theory (41.99%)
- Motion planning (13.39%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Mathematical optimization, Control theory, Motion planning, Artificial intelligence and Probabilistic logic.
His work carried out in the field of Mathematical optimization brings together such families of science as Function, Quadratic equation and Linear system.
His Control theory research is multidisciplinary, incorporating perspectives in Optimization problem and Descent.
Panagiotis Tsiotras interconnects Motion, State and Reachability in the investigation of issues within Motion planning.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Spacecraft, Dual quaternion and Computer vision.
The various areas that Panagiotis Tsiotras examines in his Probabilistic logic study include State, Distribution, Applied mathematics and Nonlinear system.
Between 2017 and 2021, his most popular works were:
- Advanced planning for autonomous vehicles using reinforcement learning and deep inverse reinforcement learning (52 citations)
- Optimal Covariance Control for Stochastic Systems Under Chance Constraints (38 citations)
- AutoRally: An Open Platform for Aggressive Autonomous Driving (30 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Mathematical analysis
Panagiotis Tsiotras focuses on Mathematical optimization, Probabilistic logic, Artificial intelligence, Control theory and Spacecraft.
The Mathematical optimization study combines topics in areas such as Divide and conquer algorithms, Multi-agent system and Linear system.
His Probabilistic logic research is multidisciplinary, relying on both State, Contrast, Applied mathematics and Nonlinear system.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning, Fuel efficiency and Intelligent transportation system.
His Control theory research integrates issues from Point and Descent.
In general Spacecraft, his work in Rendezvous is often linked to Decoupling linking many areas of study.
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