What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Mechanical engineering
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Robot, Mobile robot and Motion planning.
His study in the field of Robotics also crosses realms of Obstacle.
Sanjiv Singh interconnects Automatic vehicle location, Heading and Odometry in the investigation of issues within Computer vision.
His Robot research includes elements of Intelligent control, Key, Distributed computing and Computational resource.
The various areas that Sanjiv Singh examines in his Mobile robot study include Wireless sensor network, Real-time computing and Visual servoing.
His Motion planning study incorporates themes from Mathematical optimization, Approximation algorithm, Human operator and Ground vehicles.
His most cited work include:
- Autonomous driving in urban environments: Boss and the Urban Challenge (1101 citations)
- LOAM: Lidar Odometry and Mapping in Real-time (691 citations)
- Integrated vehicle positioning and navigation system, apparatus and method (419 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Artificial intelligence, Computer vision, Robot, Mobile robot and Real-time computing.
His Artificial intelligence research incorporates themes from Computer graphics and Remote sensing.
His Computer vision research includes themes of Visual odometry, Odometry, Robustness and Position.
His Robot study also includes
- Simulation, which have a strong connection to Automation,
- Excavator which connect with Task.
His Mobile robot study integrates concerns from other disciplines, such as Kalman filter and Motion planning.
Many of his studies on Real-time computing involve topics that are commonly interrelated, such as Wireless sensor network.
He most often published in these fields:
- Artificial intelligence (44.58%)
- Computer vision (33.73%)
- Robot (24.90%)
What were the highlights of his more recent work (between 2013-2020)?
- Artificial intelligence (44.58%)
- Computer vision (33.73%)
- Real-time computing (15.26%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Computer vision, Real-time computing, Lidar and Odometry.
His Artificial intelligence research is multidisciplinary, relying on both Sound and Computer graphics.
His Visual odometry research extends to Computer vision, which is thematically connected.
His Real-time computing research incorporates themes from Motion planning, Mobile robot, Tree, Grid and Probabilistic logic.
As a part of the same scientific family, he mostly works in the field of Motion planning, focusing on Plan and, on occasion, Satellite imagery.
The concepts of his Motion estimation study are interwoven with issues in Point cloud and Rotation.
Between 2013 and 2020, his most popular works were:
- LOAM: Lidar Odometry and Mapping in Real-time (691 citations)
- Visual-lidar odometry and mapping: low-drift, robust, and fast (272 citations)
- Low-drift and real-time lidar odometry and mapping (177 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Mechanical engineering
His scientific interests lie mostly in Artificial intelligence, Computer vision, Odometry, Lidar and Robustness.
His work in the fields of Artificial intelligence, such as Visual odometry, Image acquisition and Sensory cue, overlaps with other areas such as Vineyard and Moving vehicle.
His work on Machine vision as part of general Computer vision study is frequently linked to High resolution, bridging the gap between disciplines.
His Odometry research is multidisciplinary, incorporating perspectives in 3d laser scanner and Ego motion estimation.
His Lidar research includes themes of Motion estimation and Point cloud.
Sanjiv Singh has included themes like Simultaneous localization and mapping, Feature extraction, Rotation and Benchmark in his Motion estimation study.
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