Tim Baier
Papers
5
Total Citations
71
H-Index
4
About
Tim Baier’s research lies at the intersection of robotics, human-robot interaction, and learning by demonstration, with a particular focus on enabling service robots to understand and replicate human actions. His most influential work, “Learning of demonstrated grasping skills by stereoscopic tracking of human head configuration” (34 citations), introduces a novel approach where a multimodal service robot learns grasping skills by tracking a human instructor’s hands in real time—a key contribution to intuitive robot programming. Baier also advanced grasp evaluation with his “Reusability-based Semantics for Grasp Evaluation in Context of Service Robotics” (18 citations), proposing a criterion that moves beyond purely force-based metrics to incorporate object semantics, making grasps more human-intuitive. His work on flexible software architectures for multi-modal service robots (12 citations) further eased high-level application development through the innovative roblet-technology. Beyond technical contributions, Baier is dedicated to education, as seen in “Building and Understanding Robotics” (5 citations), a practical course designed to engage students at various levels. His early work integrating gaze and gesture detection for natural language instruction in assembly scenarios (2 citations) rounds out a career focused on making robots more accessible and capable collaborators.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3A flexible software architecture for multi-modal service robots12 citations · 2006
- 4
- 5