Lucas Janisch

Siemens (Germany), Institute of Automation

Papers

3

Total Citations

29

H-Index

3

About

Lucas Janisch is a robotics researcher focused on bridging the gap between industrial automation and flexible, user-friendly manipulation. His work centers on two key challenges: the perception of deformable objects and the simplification of robotic programming for manufacturing. Janisch’s most impactful contribution is a weakly supervised, semi-automatic image labeling approach for Deformable Linear Objects (DLOs) like wires and cables—a notoriously difficult perception problem. This work, which has garnered 23 citations, addresses a critical bottleneck in applying robotics to everyday and industrial tasks involving flexible materials. He further advances manufacturing accessibility by introducing a novel user grasp metric and a teaching approach that allows non-experts to program robotic grasping, as detailed in his 2024 paper. Janisch also explores the handling of delicate components in power electronics, demonstrating robotic manipulation of copper clips for laser bonding to enhance production flexibility. His research directly tackles the need for adaptable, easy-to-deploy robotic solutions in small and medium enterprises, making him a notable contributor to the future of flexible automation.

Research Focus

Key Achievements

3
H-Index
3
Papers
29
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
A Weakly Supervised Semi-Automatic Image Labeling Approach for Deformable Linear Objects
23 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Siemens (Germany), Institute of Automation

Top Papers

  1. 1
  2. 2
  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago