What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Computer vision
Kostas E. Bekris mainly focuses on Motion planning, Artificial intelligence, Computer vision, Mathematical optimization and Robot.
His work in the fields of Motion planning, such as Probabilistic roadmap, intersects with other areas such as Data structure.
His Artificial intelligence research includes elements of Software deployment and PATH.
His Object, Particle filter and Navigation system study in the realm of Computer vision connects with subjects such as Accelerometer and Visual impairment.
Kostas E. Bekris combines subjects such as Tree, Distributed computing and Kinodynamic planning, Mobile robot with his study of Mathematical optimization.
His Robot study combines topics from a wide range of disciplines, such as Computation and Data science.
His most cited work include:
- Robotics-based location sensing using wireless ethernet (443 citations)
- On the feasibility of using wireless ethernet for indoor localization (250 citations)
- Indoor Human Navigation Systems {a Survey (203 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Motion planning, Robot, Artificial intelligence, Mathematical optimization and Computer vision.
His study focuses on the intersection of Motion planning and fields such as Asymptotically optimal algorithm with connections in the field of Spanner.
As a member of one scientific family, Kostas E. Bekris mostly works in the field of Robot, focusing on Distributed computing and, on occasion, Real-time computing.
His work on Robotics, Object and Robotic arm as part of his general Artificial intelligence study is frequently connected to Real image and Context, thereby bridging the divide between different branches of science.
His Object study incorporates themes from Structure and Pose.
His Mathematical optimization research incorporates themes from Probabilistic logic, Graph theory, Graph and State space.
He most often published in these fields:
- Motion planning (37.63%)
- Robot (34.41%)
- Artificial intelligence (29.03%)
What were the highlights of his more recent work (between 2018-2021)?
- Robot (34.41%)
- Artificial intelligence (29.03%)
- Motion planning (37.63%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Robot, Artificial intelligence, Motion planning, Computer vision and Object.
His Robot research integrates issues from Data-driven, Distributed computing and Robotic arm.
Kostas E. Bekris is involved in the study of Artificial intelligence that focuses on Robotics in particular.
The Motion planning study combines topics in areas such as Motion, State space, Mathematical optimization, Sequence and Trajectory.
His primary area of study in Mathematical optimization is in the field of Asymptotically optimal algorithm.
His work carried out in the field of Object brings together such families of science as Representation, Pose and Task.
Between 2018 and 2021, his most popular works were:
- Probabilistic Completeness of RRT for Geometric and Kinodynamic Planning With Forward Propagation (26 citations)
- dRRT * : Scalable and informed asymptotically-optimal multi-robot motion planning (20 citations)
- Learning a State Transition Model of an Underactuated Adaptive Hand (13 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Machine learning
His primary areas of study are Robot, Motion planning, Tensegrity, Kinodynamic planning and Mathematical optimization.
The various areas that Kostas E. Bekris examines in his Robot study include Path, Theoretical computer science, Distributed computing and Robotic arm.
His work in Distributed computing covers topics such as Automation which are related to areas like Key.
Kostas E. Bekris undertakes multidisciplinary investigations into Motion planning and Motion in his work.
His Kinodynamic planning research is multidisciplinary, incorporating perspectives in Centrality and Trajectory.
His Mathematical optimization research includes themes of Workspace and Configuration space.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
