Karl Berntorp

About

Karl Berntorp is a leading researcher in autonomous vehicle motion planning, state estimation, and control, with a focus on probabilistic and safety-critical methods. His major contributions include pioneering the use of particle filtering for real-time motion planning, as described in his most-cited paper (52 citations), which leverages the inherent structure of road networks to enable efficient decision-making. He also developed a framework for integrated motion planning and control using positive invariant sets (37 citations), guaranteeing collision-free trajectories. Berntorp’s work on reachability-based decision-making (26 citations) has been validated experimentally, bridging theory and practice in automated driving. His doctoral thesis (16 citations) advanced particle filtering and optimal control for vehicles, addressing challenges like out-of-sequence measurements. Beyond autonomous driving, he has contributed to sensor fusion for mobile robots (14 citations), occupancy-grid SLAM using Rao-Blackwellized particle smoothing (8 citations), and state estimation for legged robots (5 citations). With over 170 total citations across his top papers, Berntorp’s research is highly influential in robotics and automotive engineering, offering practical solutions for safe, real-time autonomy.

Research Focus

Key Achievements

Top Papers

1. 1
   Motion Planning of Autonomous Road Vehicles by Particle Filtering

   52 citations · 2019
2. 2
   Positive Invariant Sets for Safe Integrated Vehicle Motion Planning and Control

   37 citations · 2019
3. 3
   Reachability-Based Decision-Making for Autonomous Driving: Theory and Experiments

   26 citations · 2020
4. 4
   Particle Filtering and Optimal Control for Vehicles and Robots

   16 citations · 2014
5. 5
   Sensor fusion for motion estimation of mobile robots with compensation for out-of-sequence measurements

   14 citations · 2011
6. 6
   Mobile manipulation with a kinematically redundant manipulator for a pick-and-place scenario

   9 citations · 2012
7. 7
   Rao-Blackwellized Particle Smoothing for Occupancy-Grid Based SLAM Using Low-Cost Sensors

   8 citations · 2014
8. 8
   Simultaneous State Estimation and Contact Detection for Legged Robots by Multiple-Model Kalman Filtering

   5 citations · 2024
9. 9
   Particle Filtering for Automotive: A survey

   5 citations · 2019
10. 10
    Sampling-based algorithms for optimal motion planning using closed-loop prediction

    4 citations · 2017

Key Collaborators

Contact & Links