Marco Reisert

About

Marco Reisert is a leading researcher in tactile sensing, robotic manipulation, and geometric data processing. His work bridges the gap between low-resolution sensor data and high-level object recognition, most notably through his pioneering application of bag-of-features techniques to tactile sensor arrays. In his highly cited 2009 paper (197 citations), Reisert demonstrated that even coarse tactile images from robotic fingertips can be used for robust object identification, drawing inspiration from computer vision's bag-of-words paradigm. This contribution has had lasting impact on the field of robotic haptics, enabling more intelligent and adaptive grasping systems. Beyond tactile sensing, Reisert has also advanced the mathematical foundations of rotation estimation on the 2-sphere, developing fast and accurate methods for aligning spherical data without requiring explicit point correspondences. His work is characterized by a fusion of practical robotics with rigorous geometric and statistical modeling, making him a key figure in the development of sensor-driven autonomous systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Object identification with tactile sensors using bag-of-features

   197 citations · 2009
2. 2
   Fast and Accurate Rotation Estimation on the 2-Sphere without Correspondences

   9 citations · 2008

Key Collaborators

Contact & Links