Jan Carius

About

Jan Carius is a leading roboticist whose work bridges the gap between theoretical motion planning and real-world autonomous deployment. His primary research areas include legged locomotion, trajectory optimization, and autonomous exploration, with a particular focus on enabling robots to operate in complex, contact-rich environments. Carius is best known for his central role in the CERBERUS team, which won the DARPA Subterranean Challenge by deploying a heterogeneous fleet of legged and aerial robots to autonomously explore dark, GPS-denied tunnels and urban search-and-rescue settings—a landmark achievement in field robotics (130+ combined citations). His foundational contributions to trajectory optimization include pioneering methods that implicitly handle hard contacts and even allow for controlled slipping, enabling more dynamic and physically consistent motions for legged systems (over 115 citations). He has also advanced stochastic optimal control for high-dimensional robots and co-developed TacSL, a library for visuotactile sensor simulation. With a publication record spanning top venues and a demonstrated ability to translate theory into award-winning field deployments, Carius stands out as a researcher who both pushes algorithmic frontiers and proves their worth in the world’s most challenging robotic competitions.

Research Focus

Key Achievements

Top Papers

1. 1
   CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge

   109 citations · 2022
2. 2
   Trajectory Optimization With Implicit Hard Contacts

   69 citations · 2018
3. 3
   Trajectory Optimization for Legged Robots With Slipping Motions

   47 citations · 2019
4. 4
   Deployment of an autonomous mobile manipulator at MBZIRC

   35 citations · 2018
5. 5
   Constrained stochastic optimal control with learned importance sampling: A path integral approach

   24 citations · 2021
6. 6
   CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge

   21 citations · 2022
7. 7
   Contact-Implicit Trajectory Optimization for Dynamic Object Manipulation

   20 citations · 2019
8. 8
   TacSL: A Library for Visuotactile Sensor Simulation and Learning

   15 citations · 2025
9. 9
   Autonomous Mission with a Mobile Manipulator—A Solution to the MBZIRC

   7 citations · 2017
10. 10
    Imitation Learning from MPC for Quadrupedal Multi-Gait Control

    5 citations · 2021

Key Collaborators

Contact & Links