Wolfgang Bottcher
Papers
1
Total Citations
11
H-Index
1
About
Wolfgang Bottcher is a leading researcher in the field of robotic perception, with a primary focus on haptic object recognition and the integration of tactile sensing into autonomous systems. His major contribution lies in demonstrating how robots can leverage high-quality tactile time series data to supplement visual information, enabling more robust physical interaction with their environments. In his most cited work, Bottcher systematically investigates the application of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks for classifying objects based solely on haptic feedback, achieving 11 citations and establishing a foundational methodology for tactile-based robotic intelligence. His research directly addresses a critical gap in robotics: the need for reliable object recognition when vision is occluded or unreliable. By advancing neural network architectures for processing sequential tactile data, Bottcher’s work has significant implications for dexterous manipulation, industrial automation, and assistive robotics. His contributions are essential reading for students and researchers exploring multimodal perception and the growing role of touch in next-generation robotic systems.
Research Focus
Key Achievements
Top Papers
- 1