David von Wrangel

IIT@MIT, Massachusetts Institute of Technology

Papers

Total Citations

149

H-Index

About

David von Wrangel is a rising star in robotics, whose work tackles the fundamental challenge of motion planning in cluttered, real-world environments. His research lies at the intersection of optimization, control, and artificial intelligence, with a focus on enabling robots—from agile quadrotors to articulated manipulators—to navigate complex spaces safely and efficiently. Von Wrangel’s major contribution is the development of convex optimization frameworks for nonconvex trajectory planning. His seminal 2023 paper, "Motion planning around obstacles with convex optimization," which has already garnered 145 citations, demonstrates how to reformulate the inherently nonconvex problem of obstacle avoidance into a tractable convex program, dramatically improving computational speed and reliability. Building on this, his 2024 work, "Using Graphs of Convex Sets to Guide Nonconvex Trajectory Optimization," introduces a novel method that combines discrete decision-making (e.g., choosing to go left or right around an obstacle) with continuous trajectory refinement. This hybrid approach bridges the gap between high-level reasoning and low-level control, offering a principled path to more autonomous and adaptable robots. Von Wrangel’s work is not only theoretically elegant but also practically impactful, promising to accelerate the deployment of robots in logistics, manufacturing, and urban environments.