Lorenz T. Biegler

Papers

Total Citations

103

H-Index

About

Lorenz T. Biegler is a leading figure in trajectory optimization and multi-robot motion planning, with a focus on contact-rich dynamics and scalable coordination. His major contributions include pioneering contact-implicit trajectory optimization using orthogonal collocation, a method that dramatically improves accuracy for dynamic robots with intermittent contact—eliminating the need for a priori mode scheduling. This work, his most cited with 72 citations, has become foundational for legged locomotion and manipulation. Biegler also developed Conflict-Based Model Predictive Control (CB-MPC), a scalable algorithm for multi-robot motion planning that resolves continuous-space conflicts via a modified conflict tree, earning 20 citations since 2024. Additionally, he applied receding horizon optimization to the classic Cops and Robbers problem in complex obstacle environments. His research bridges rigorous numerical methods and practical robotics, enabling more agile, autonomous systems. Biegler’s work is widely recognized for its impact on both theoretical optimization and real-world robotic applications, making him a key resource for students and researchers in motion planning and control.