What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Algorithm
His primary scientific interests are in Artificial intelligence, Robot, Mobile robot, Motion planning and Computer vision.
His study explores the link between Artificial intelligence and topics such as Markov decision process that cross with problems in State.
His Robot study combines topics from a wide range of disciplines, such as Sensor fusion and Human–computer interaction.
His Mobile robot research includes elements of Real-time computing and Position.
His studies in Motion planning integrate themes in fields like Simulation, Mathematical optimization and Trajectory.
His studies deal with areas such as Visual navigation, Novelty detection, Odometry, Robot kinematics and Visual odometry as well as Computer vision.
His most cited work include:
- Toward Optimal Active Learning through Sampling Estimation of Error Reduction (756 citations)
- MINERVA: a second-generation museum tour-guide robot (558 citations)
- Towards robotic assistants in nursing homes: Challenges and results (525 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Artificial intelligence, Robot, Machine learning, Human–computer interaction and Computer vision.
He works mostly in the field of Artificial intelligence, limiting it down to topics relating to Partially observable Markov decision process and, in certain cases, Domain knowledge, as a part of the same area of interest.
In Robot, he works on issues like Natural language, which are connected to Inference.
His research ties Human–robot interaction and Human–computer interaction together.
He has researched Computer vision in several fields, including Simultaneous localization and mapping and Motion planning.
His study looks at the relationship between Motion planning and topics such as Trajectory, which overlap with Mathematical optimization.
He most often published in these fields:
- Artificial intelligence (54.69%)
- Robot (31.56%)
- Machine learning (15.31%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (54.69%)
- Robot (31.56%)
- Task (8.75%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Artificial intelligence, Robot, Task, Machine learning and Motion planning.
His research investigates the connection between Artificial intelligence and topics such as Computer vision that intersect with problems in Sequence.
His research integrates issues of Object, Representation, Natural language and Human–computer interaction in his study of Robot.
His research in Human–computer interaction intersects with topics in Semantic memory, Estimation, Natural language understanding and Human–robot interaction.
His study in Machine learning is interdisciplinary in nature, drawing from both Stimulus, Training set, Baseline and Psychophysics.
His Motion planning study combines topics in areas such as Real-time computing, Mathematical optimization, Theoretical computer science and Metric.
Between 2017 and 2021, his most popular works were:
- Bayesian Learning for Safe High-Speed Navigation in Unknown Environments (49 citations)
- Asymptotically Optimal Planning under Piecewise-Analytic Constraints (40 citations)
- Efficient grounding of abstract spatial concepts for natural language interaction with robot platforms (26 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Algorithm
Nicholas Roy spends much of his time researching Robot, Artificial intelligence, Natural language, Obstacle avoidance and Motion planning.
His study in the fields of Mobile robot under the domain of Robot overlaps with other disciplines such as Grippers.
His Mobile robot study incorporates themes from Probabilistic logic, Object type and Phrase, Natural language processing.
He has included themes like Machine learning, Computer vision and Sequence in his Artificial intelligence study.
Within one scientific family, Nicholas Roy focuses on topics pertaining to Human–computer interaction under Natural language, and may sometimes address concerns connected to Natural language interaction, Representation, Human–robot interaction and Robot learning.
His research in Motion planning tackles topics such as Real-time computing which are related to areas like Pose, Autonomous system and Search and rescue.
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