What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Programming language
Tomás Lozano-Pérez spends much of his time researching Artificial intelligence, Computer vision, Motion planning, Robot and Robotics.
His work deals with themes such as Machine learning and Task, which intersect with Artificial intelligence.
His Computer vision research incorporates themes from Polyhedron, Surface and Pattern recognition.
His Motion planning research incorporates elements of GRASP, Mobile robot, Control engineering, Extension and Trajectory.
His study in Robot is interdisciplinary in nature, drawing from both Algorithm, Degrees of freedom, Control theory and Configuration space.
He works mostly in the field of Robotics, limiting it down to concerns involving Representation and, occasionally, Workspace and Manipulator.
His most cited work include:
- Solving the multiple instance problem with axis-parallel rectangles (2009 citations)
- An algorithm for planning collision-free paths among polyhedral obstacles (1970 citations)
- A Framework for Multiple-Instance Learning (1001 citations)
What are the main themes of his work throughout his whole career to date?
Tomás Lozano-Pérez focuses on Artificial intelligence, Robot, Motion planning, Computer vision and Task.
His work on Object, Robotics and Representation as part of general Artificial intelligence research is frequently linked to Set, thereby connecting diverse disciplines of science.
His Robot study deals with Mathematical optimization intersecting with Algorithm.
His biological study spans a wide range of topics, including Workspace, Theoretical computer science, Mobile robot and Configuration space.
Tomás Lozano-Pérez works mostly in the field of Computer vision, limiting it down to topics relating to Polyhedron and, in certain cases, Face, as a part of the same area of interest.
His Task research focuses on State and how it relates to Construct.
He most often published in these fields:
- Artificial intelligence (54.75%)
- Robot (33.03%)
- Motion planning (24.43%)
What were the highlights of his more recent work (between 2016-2021)?
- Robot (33.03%)
- Artificial intelligence (54.75%)
- Task (19.00%)
In recent papers he was focusing on the following fields of study:
His main research concerns Robot, Artificial intelligence, Task, Motion planning and Object.
The various areas that Tomás Lozano-Pérez examines in his Robot study include State, Human–computer interaction, Mathematical optimization, Task analysis and Sequence.
Artificial intelligence is frequently linked to Modular design in his study.
His studies deal with areas such as Variety and Operator as well as Task.
His Motion planning research includes elements of Workspace, Active learning, Computer vision and Domain.
The study incorporates disciplines such as Motion and Machine learning in addition to Object.
Between 2016 and 2021, his most popular works were:
- From Skills to Symbols: Learning Symbolic Representations for Abstract High-Level Planning (89 citations)
- FFRob: Leveraging symbolic planning for efficient task and motion planning: (61 citations)
- Modular meta-learning. (39 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Machine learning
His primary areas of investigation include Robot, Artificial intelligence, Task, Motion planning and Theoretical computer science.
His work carried out in the field of Robot brings together such families of science as GRASP, Artificial neural network, Object, Task analysis and Sequence.
His Artificial intelligence study integrates concerns from other disciplines, such as Computer vision and Modular design.
His research investigates the link between Computer vision and topics such as Belief state that cross with problems in Control and Image.
His work investigates the relationship between Task and topics such as State that intersect with problems in Machine learning and Operator.
His research integrates issues of Domain, Graph, Construct, Probabilistic logic and Computation in his study of Theoretical computer science.
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