What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Mechanical engineering
- Computer vision
His scientific interests lie mostly in Artificial intelligence, Mobile robot, Simulation, Motion planning and Human–computer interaction.
His work in the fields of Artificial intelligence, such as Robotics, Robot and Feature extraction, overlaps with other areas such as Boundary.
His Robot study combines topics in areas such as Wireless sensor network, Distributed computing and Sensor array.
His Mobile robot research is multidisciplinary, incorporating elements of Planner, Transport engineering, Service and Robustness.
His Simulation research is multidisciplinary, relying on both Acoustics, Limiting, Clamping and Signal.
His biological study spans a wide range of topics, including Mobile robot navigation and Alternative process.
His most cited work include:
- A Brain Controlled Wheelchair to Navigate in Familiar Environments (292 citations)
- Why Robots? A Survey on the Roles and Benefits of Social Robots in the Therapy of Children with Autism (263 citations)
- Controlling a Wheelchair Indoors Using Thought (204 citations)
What are the main themes of his work throughout his whole career to date?
Marcelo H. Ang spends much of his time researching Artificial intelligence, Robot, Control theory, Control engineering and Computer vision.
His research integrates issues of Lidar and Machine learning in his study of Artificial intelligence.
Marcelo H. Ang has included themes like Artificial neural network and Simulation in his Robot study.
The Control theory study combines topics in areas such as Vibration control and Motion control.
Marcelo H. Ang interconnects Control system, Control, Robot end effector and Actuator in the investigation of issues within Control engineering.
His Mobile robot study integrates concerns from other disciplines, such as Transport engineering and Motion planning.
He most often published in these fields:
- Artificial intelligence (35.60%)
- Robot (34.30%)
- Control theory (23.30%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (35.60%)
- Computer vision (20.39%)
- Point cloud (4.21%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Point cloud, Robot and Object.
In his study, Marcelo H. Ang carries out multidisciplinary Artificial intelligence and Scale research.
His Computer vision research incorporates themes from Lidar and Robustness.
His Point cloud research incorporates elements of Ground truth, Task, Data mining and Algorithm.
His work on Soft robotics as part of general Robot research is frequently linked to On demand, bridging the gap between disciplines.
His Segmentation study combines topics in areas such as Augmented reality, Streak and Mobile robot.
Between 2017 and 2021, his most popular works were:
- A General Pipeline for 3D Detection of Vehicles (80 citations)
- Autonomous Exploration and Mapping System Using Heterogeneous UAVs and UGVs in GPS-Denied Environments (36 citations)
- Cascaded Refinement Network for Point Cloud Completion (24 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mechanical engineering
- Computer vision
His primary areas of investigation include Artificial intelligence, Computer vision, Object, Point cloud and Convolutional neural network.
In general Artificial intelligence study, his work on Feature extraction and Image often relates to the realm of Point, thereby connecting several areas of interest.
His study looks at the relationship between Computer vision and topics such as Lidar, which overlap with Robustness, Particle filter, Histogram, Reflectivity and Pipeline.
Marcelo H. Ang focuses mostly in the field of Point cloud, narrowing it down to matters related to Ground truth and, in some cases, Algorithm and Point distribution model.
His Convolutional neural network study incorporates themes from Robot and Motion planning.
The study incorporates disciplines such as Pipeline transport, Semantic mapping, Control reconfiguration and Distributed computing in addition to Robot.
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