2023 - Research.com Computer Science in Germany Leader Award
2014 - IEEE Fellow For contributions to haptic telepresence systems and autonomous robots
Martin Buss spends much of his time researching Artificial intelligence, Simulation, Haptic technology, Robot and Computer vision. Artificial intelligence and Pattern recognition are commonly linked in his work. His biological study spans a wide range of topics, including Real-time computing and Control theory, Trajectory.
He has researched Control theory in several fields, including Mathematical optimization and Stiffness. The study incorporates disciplines such as Control engineering, Teleoperation, Perception and Actuator in addition to Haptic technology. His work deals with themes such as Cognition and Exoskeleton, which intersect with Robot.
Martin Buss mainly investigates Artificial intelligence, Control theory, Robot, Haptic technology and Simulation. The Artificial intelligence study combines topics in areas such as Perception, Computer vision and Pattern recognition. His work in Control theory addresses issues such as Control engineering, which are connected to fields such as Robustness, Control and Stability.
Martin Buss frequently studies issues relating to Trajectory and Robot. His studies deal with areas such as Telerobotics, Task, Virtual reality, Human–computer interaction and Teleoperation as well as Haptic technology. The study incorporates disciplines such as Workspace and Actuator in addition to Simulation.
His main research concerns Control theory, Robot, Artificial intelligence, Mathematical optimization and Control theory. His research investigates the connection with Robot and areas like Object which intersect with concerns in Haptic technology. Martin Buss combines subjects such as Algorithm and Computer vision with his study of Artificial intelligence.
His Mathematical optimization study combines topics in areas such as Control and Computation. His Underactuation study in the realm of Control theory interacts with subjects such as Oscillation. As a part of the same scientific study, he usually deals with the Torque, concentrating on Simulation and frequently concerns with Throwing.
His primary scientific interests are in Control theory, Artificial intelligence, Mathematical optimization, Robot and Computer vision. His study explores the link between Control theory and topics such as Computational complexity theory that cross with problems in Spline interpolation and Torque. His research on Artificial intelligence frequently connects to adjacent areas such as Human–computer interaction.
His work on Pontryagin's minimum principle and Optimal control is typically connected to Node and Control as part of general Mathematical optimization study, connecting several disciplines of science. Martin Buss interconnects Nash equilibrium, Task, Trajectory and Decision model in the investigation of issues within Robot. His study in Computer vision is interdisciplinary in nature, drawing from both Occupancy grid mapping and Representation.
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Feature Extraction and Selection for Emotion Recognition from EEG
Robert Jenke;Angelika Peer;Martin Buss.
IEEE Transactions on Affective Computing (2014)
Compliant actuation of rehabilitation robots
H. Vallery;J. Veneman;E. van Asseldonk;R. Ekkelenkamp.
IEEE Robotics & Automation Magazine (2008)
HUMAN–ROBOT COLLABORATION: A SURVEY
Andrea Maria Bauer;Dirk Wollherr;Martin Buss.
International Journal of Humanoid Robotics (2008)
Dextrous hand grasping force optimization
M. Buss;H. Hashimoto;J.B. Moore.
international conference on robotics and automation (1996)
Multiclass Common Spatial Patterns and Information Theoretic Feature Extraction
M. Grosse-Wentrup;M. Buss.
IEEE Transactions on Biomedical Engineering (2008)
Bilateral teleoperation over the internet: the time varying delay problem
N. Chopra;M.W. Spong;S. Hirche;M. Buss.
american control conference (2003)
Comparison of surface normal estimation methods for range sensing applications
Klaas Klasing;Daniel Althoff;Dirk Wollherr;Martin Buss.
international conference on robotics and automation (2009)
Model-Based Probabilistic Collision Detection in Autonomous Driving
M. Althoff;O. Stursberg;M. Buss.
IEEE Transactions on Intelligent Transportation Systems (2009)
Reachability analysis of nonlinear systems with uncertain parameters using conservative linearization
M. Althoff;O. Stursberg;M. Buss.
conference on decision and control (2008)
Real-time 3D hand gesture interaction with a robot for understanding directions from humans
Michael Van den Bergh;Daniel Carton;Roderick De Nijs;Nikos Mitsou.
robot and human interactive communication (2011)
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