Christoph Sprunk

About

Christoph Sprunk is a prominent robotics researcher whose work spans mobile robot navigation, motion planning, and human-robot interaction. His most celebrated contribution lies in the domain of socially compliant navigation, where his 2016 paper on inverse reinforcement learning to model cooperative human navigation behavior has garnered an impressive 469 citations, establishing him as a leading voice in enabling robots to understand and respect unspoken social norms in shared environments. Complementing this, his early work on predicting pedestrian trajectories for socially aware navigation (210 citations) laid important groundwork for robots operating alongside humans. Sprunk has also made significant technical contributions to kinodynamic motion planning, pioneering spline-based trajectory generation methods — including quintic Bézier splines for omnidirectional robots — that allow mobile platforms to navigate efficiently while respecting physical constraints. His research on grid-based spatial representations (132 citations) and particle filter-based localization accuracy (125 citations) reflects deep expertise in robust robot perception and mapping in dynamic environments. Notably, his lidar-based teach-and-repeat system demonstrates a strong applied focus, bringing intuitive robot programming to industrial settings. Across his career, Sprunk has consistently bridged theoretical innovation and real-world deployment, making lasting contributions to both academic robotics and practical autonomous systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Socially compliant mobile robot navigation via inverse reinforcement learning

   469 citations · 2016
2. 2
   Feature-Based Prediction of Trajectories for Socially Compliant Navigation

   210 citations · 2012
3. 3
   Kinodynamic motion planning for mobile robots using splines

   138 citations · 2009
4. 4
   Efficient grid-based spatial representations for robot navigation in dynamic environments

   132 citations · 2012
5. 5
   On the position accuracy of mobile robot localization based on particle filters combined with scan matching

   125 citations · 2012
6. 6
   An accurate and efficient navigation system for omnidirectional robots in industrial environments

   77 citations · 2016
7. 7
   Online generation of kinodynamic trajectories for non-circular omnidirectional robots

   48 citations · 2011
8. 8
   Lidar-based teach-and-repeat of mobile robot trajectories

   45 citations · 2013
9. 9
   Feature-Based Prediction of Trajectories for Socially Compliant Navigation

   44 citations · 2013
10. 10
    Online generation of homotopically distinct navigation paths

    42 citations · 2014

Key Collaborators

Contact & Links