What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Robot
- Control theory
His primary areas of study are Robot, Control theory, Simulation, Robot control and Control engineering.
His Robot research is under the purview of Artificial intelligence.
His study looks at the intersection of Control theory and topics like Solver with Robot end effector, Nonlinear programming, Model predictive control and Optimal control.
His Simulation research is multidisciplinary, relying on both Flexibility, Quadrupedal robot and Mobile robot.
His work investigates the relationship between Quadrupedal robot and topics such as Robustness that intersect with problems in Computer vision.
While the research belongs to areas of Control engineering, Marco Hutter spends his time largely on the problem of Torque, intersecting his research to questions surrounding Actuator.
His most cited work include:
- Robust visual inertial odometry using a direct EKF-based approach (371 citations)
- Learning agile and dynamic motor skills for legged robots (292 citations)
- ANYmal - a highly mobile and dynamic quadrupedal robot (203 citations)
What are the main themes of his work throughout his whole career to date?
Robot, Control theory, Artificial intelligence, Computer vision and Terrain are his primary areas of study.
His studies deal with areas such as Control engineering, Control theory and Model predictive control as well as Robot.
His Control theory study frequently links to other fields, such as Robot control.
His study in the field of Robotics, Reinforcement learning, Robustness and Artificial neural network is also linked to topics like Quadrupedalism.
Marco Hutter has included themes like Robot kinematics and Odometry in his Computer vision study.
His Torque study which covers Simulation that intersects with Quadrupedal robot.
He most often published in these fields:
- Robot (65.48%)
- Control theory (32.99%)
- Artificial intelligence (32.49%)
What were the highlights of his more recent work (between 2020-2021)?
- Robot (65.48%)
- Artificial intelligence (32.49%)
- Model predictive control (12.18%)
In recent papers he was focusing on the following fields of study:
Marco Hutter mainly focuses on Robot, Artificial intelligence, Model predictive control, Computer vision and Control theory.
His work carried out in the field of Robot brings together such families of science as Control engineering and State.
His Artificial intelligence research incorporates elements of Hybrid system and Bellman equation.
His Model predictive control research includes elements of Mobile manipulator, Selection and Benchmark.
In general Computer vision study, his work on Rendering, Surfel, Image and Point cloud often relates to the realm of GRASP, thereby connecting several areas of interest.
His study in the fields of Optimal control, Kalman filter and System dynamics under the domain of Control theory overlaps with other disciplines such as Collision avoidance.
Between 2020 and 2021, his most popular works were:
- Perceptive whole‐body planning for multilegged robots in confined spaces (3 citations)
- Constraint Handling in Continuous-Time DDP-Based Model Predictive Control. (2 citations)
- A Unified MPC Framework for Whole-Body Dynamic Locomotion and Manipulation (1 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Robot
- Robotics
Marco Hutter spends much of his time researching Robot, Human–computer interaction, Pipeline, Model predictive control and Mobile manipulator.
His Robot study is concerned with the larger field of Artificial intelligence.
His Human–computer interaction study integrates concerns from other disciplines, such as Motion controller and Motion planning.
Other disciplines of study, such as Task, Plan, Workspace, Sequence and Object, are mixed together with his Pipeline studies.
The Model predictive control study combines topics in areas such as Differential dynamic programming, Mathematical optimization, Linear quadratic and Trajectory optimization.
His research integrates issues of Robot kinematics and Robustness in his study of Mobile manipulator.
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