About

Brian J. Driessen’s research focuses on the intersection of robotics, control theory, and optimization, with a particular emphasis on developing advanced observer/controller systems for robotic manipulators. His major contributions include pioneering work on globally exponential and adaptive controllers that enable precise position tracking in robots without requiring velocity measurements—a significant challenge in robotics. Driessen has also addressed complex scenarios involving hysteretic joint friction, DC motor dynamics, and unknown link/actuator parameters, proving global convergence to zero tracking error in his adaptive controllers. His most cited work, “Analyzing the Multiple-target-multiple-agent Scenario Using Optimal Assignment Algorithms” (52 citations), tackles the optimal deployment of mobile robots with limited sensor range and travel distances. Additionally, his research on minimum-time control for systems with Coulomb friction, using mixed integer linear programming to find near-global optima, demonstrates his versatility in solving challenging optimization problems. With a career spanning over two decades, Driessen’s publications have accumulated substantial citations, reflecting their lasting impact on the fields of robotics and nonlinear control.

Research Focus

Key Achievements

6
H-Index
13
Papers
139
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Analyzing the Multiple-target-multiple-agent Scenario Using Optimal Assignment Algorithms
52 citations · 2002
📈 Most Prolific Year: 2002 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Sandia National Laboratories, Wichita State University, Sandia National Laboratories California, University of Alabama in Huntsville

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago