What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Computer vision
His primary scientific interests are in Mobile robot, Robot, Artificial intelligence, Control engineering and Control theory.
The Mobile robot study combines topics in areas such as Kalman filter, Wireless sensor network and Motion planning.
His study in Robot is interdisciplinary in nature, drawing from both Distributed computing, Simulation and Robustness.
He interconnects Real-time computing and Nonholonomic system in the investigation of issues within Simulation.
His work focuses on many connections between Artificial intelligence and other disciplines, such as Computer vision, that overlap with his field of interest in Cooperative perception.
His work carried out in the field of Control engineering brings together such families of science as Control, Model predictive control, Fault detection and isolation, Observer and Actuator.
His most cited work include:
- An Unmanned Aircraft System for Automatic Forest Fire Monitoring and Measurement (250 citations)
- Experimental Results in Multi-UAV Coordination for Disaster Management and Civil Security Applications (242 citations)
- Autonomous transportation and deployment with aerial robots for search and rescue missions (240 citations)
What are the main themes of his work throughout his whole career to date?
Anibal Ollero mostly deals with Artificial intelligence, Robot, Control engineering, Real-time computing and Mobile robot.
His Artificial intelligence study often links to related topics such as Computer vision.
His Robot research includes elements of Distributed computing and Robustness.
His Control engineering study integrates concerns from other disciplines, such as Control and Control theory.
His Real-time computing research is multidisciplinary, relying on both Testbed, Wireless sensor network and Simulation.
His Motion planning research extends to the thematically linked field of Mobile robot.
He most often published in these fields:
- Artificial intelligence (24.96%)
- Robot (23.89%)
- Control engineering (19.96%)
What were the highlights of his more recent work (between 2018-2021)?
- Robot (23.89%)
- Artificial intelligence (24.96%)
- Real-time computing (19.25%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Robot, Artificial intelligence, Real-time computing, Control theory and Robotics.
Anibal Ollero has included themes like Flapping wing, Motion blur, Control engineering, Robotic arm and Manipulator in his Robot study.
His studies in Artificial intelligence integrate themes in fields like Positioning system, Trajectory and Computer vision.
His Real-time computing research focuses on subjects like Sensor fusion, which are linked to Undersampling.
His study in the field of Control theory and Control system also crosses realms of Riccati equation.
His studies deal with areas such as Systems engineering and Modular design as well as Robotics.
Between 2018 and 2021, his most popular works were:
- Robotic System for Inspection by Contact of Bridge Beams Using UAVs (27 citations)
- Novel Aerial Manipulator for Accurate and Robust Industrial NDT Contact Inspection: A New Tool for the Oil and Gas Inspection Industry. (17 citations)
- Sensor Installation and Retrieval Operations using an Unmanned Aerial Manipulator (16 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Mechanical engineering
His main research concerns Artificial intelligence, Robot, Real-time computing, Computer vision and Autopilot.
Anibal Ollero combines subjects such as Trajectory and GRASP with his study of Artificial intelligence.
His Robot manipulator study, which is part of a larger body of work in Robot, is frequently linked to Nondestructive testing, bridging the gap between disciplines.
His Real-time computing study combines topics from a wide range of disciplines, such as Automation, Manipulator, Task, Multirotor and Event.
The various areas that he examines in his Computer vision study include Energy consumption, Visual perception and DUAL.
Control engineering covers he research in Control theory.
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