Henry Bradlow

University of California, Berkeley

Papers

2

Total Citations

1,269

H-Index

2

About

Henry Bradlow is a leading figure in robotic motion planning, renowned for pioneering optimization-based approaches that enable robots to navigate complex, obstacle-filled environments. His key research areas include trajectory optimization, collision avoidance, and sequential convex programming. Bradlow’s major contributions are encapsulated in two landmark papers. His 2014 work, "Motion planning with sequential convex optimization and convex collision checking," has garnered over 840 citations, introducing a robust framework that refines naïve, collision-prone paths into smooth, feasible trajectories. Building on this, his 2013 paper, "Finding Locally Optimal, Collision-Free Trajectories with Sequential Convex Optimization," with 429 citations, innovatively integrates collision avoidance into trajectory optimization by penalizing collisions with a hinge loss function. This work significantly advanced the field by providing a computationally efficient method for generating locally optimal paths. Bradlow’s algorithms, which extend the capabilities of earlier methods like CHOMP, have become foundational in robotics, influencing both academic research and practical applications in autonomous systems. His achievements underscore a transformative impact on how robots perceive and move through their surroundings.

Research Focus

Key Achievements

2
H-Index
2
Papers
1,269
Total Citations
635
Avg Citations/Paper
🏆 Most Cited Paper
Motion planning with sequential convex optimization and convex collision checking
840 citations · 2014
📈 Most Prolific Year: 2014 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University of California, Berkeley

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago