Frank B. ter Haar
Papers
3
Total Citations
33
H-Index
3
About
Frank B. ter Haar is a researcher at the forefront of human-robot interaction and intelligent robotic perception. His work centers on enhancing teleoperation systems by integrating multimodal sensory feedback and adaptive machine learning. A key contribution is his exploration of how environmental information impacts spatial task performance and operator situation awareness during virtual reality (VR) mediated teleoperation, a study that has garnered 19 citations. He has also advanced mobile robotics through incremental learning-based adaptive object recognition, enabling robots to better understand and navigate unknown 3D environments. Pushing the boundaries of sensory feedback, ter Haar introduced thermal feedback in VR robot teleoperation, allowing operators to “feel” temperature during remote tasks—a proof-of-concept that earned 6 citations. His research uniquely bridges the gap between human perceptual needs and robotic autonomy, with notable achievements including the integration of stereo cameras, 360° cameras, and long-wave infrared sensors into a unified teleoperation demonstrator. By improving situation awareness and adaptability, ter Haar’s work is paving the way for more intuitive and effective human-robot collaboration in complex, real-world settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2Incremental Learning-Based Adaptive Object Recognition for Mobile Robots8 citations · 2018
- 3Grasping Temperature: Thermal Feedback in VR Robot Teleoperation6 citations · 2022