Papers
70
Total Citations
1,862
H-Index
19
About
Mark Campbell is a pioneering robotics and autonomous systems researcher whose work has fundamentally shaped how machines perceive, navigate, and make decisions in complex environments. Best known for his contributions to autonomous vehicle technology, Campbell gained significant recognition through his involvement in the 2007 DARPA Urban Challenge, which produced two of his most influential papers — including a landmark survey on urban autonomous driving (350 citations) and a celebrated forensic analysis of the historic MIT-Cornell vehicle collision (76 citations). His research spans probabilistic planning and prediction, demonstrated through his contingency-based path planner for handling dynamic obstacle uncertainty (129 citations) and probabilistic anticipation algorithms for urban robots (64 citations). Campbell has also advanced real-time stereo depth estimation for resource-constrained systems (208 citations), modular robot autonomy (110 citations), and distributed data fusion across multi-agent networks (56 citations). His Bayesian frameworks for human-robot collaboration further highlight his commitment to bridging human intuition with machine intelligence. With over 980 citations across his top works alone, Campbell's research has left an enduring mark on robotics, consistently translating rigorous theory into real-world autonomous systems of remarkable capability.
Research Focus
Key Achievements
Top Papers
- 1Autonomous driving in urban environments: approaches, lessons and challenges350 citations · 2010
- 2Anytime Stereo Image Depth Estimation on Mobile Devices208 citations · 2019
- 3
- 4An integrated system for perception-driven autonomy with modular robots110 citations · 2018
- 5
- 6The MIT–Cornell collision and why it happened76 citations · 2008
- 7
- 8Bayesian Multicategorical Soft Data Fusion for Human–Robot Collaboration64 citations · 2012
- 9
- 10Using Stream Functions for Complex Behavior and Path Generation44 citations · 2003