About

Thomas M. Howard is a pioneering roboticist whose research spans autonomous mobile robot navigation, model-predictive motion planning, and robotic manipulation. His most influential work focuses on enabling robots to navigate complex, unstructured environments with remarkable efficiency and adaptability. Howard's 2007 paper on optimal rough terrain trajectory generation for wheeled mobile robots (368 citations) established a landmark framework for generalizing motion planning across diverse vehicle types, using numerical linearization to model propulsion and suspension dynamics. Building on this, his subsequent work on state space sampling (206 citations) and model-predictive motion planning (107 citations) significantly advanced how autonomous robots anticipate and respond to complex environmental constraints under real-world computational limitations. Beyond ground robotics, Howard contributed to aerial manipulation, co-authoring early research on UAVs capable of physical wall interaction—a novel frontier in autonomous flight. His contributions to dexterous manipulation through the DARPA Autonomous Robotic Manipulation program, alongside tactile-based object localization and sensor-guided manipulation frameworks, demonstrate a remarkably broad research portfolio. His work, accumulating over 1,000 citations across foundational publications, has meaningfully shaped both theoretical and applied robotics, making him an essential reference point for researchers studying autonomous navigation, motion planning, and robot-environment interaction.

Research Focus

Key Achievements

15
H-Index
26
Papers
1,386
Total Citations
53
Avg Citations/Paper
🏆 Most Cited Paper
Optimal Rough Terrain Trajectory Generation for Wheeled Mobile Robots
368 citations · 2007
📈 Most Prolific Year: 2010 (4 Papers)
🤝 Key Collaborators: 74
🏛 Institutions: Carnegie Mellon University, Karlsruhe Institute of Technology, Massachusetts Institute of Technology, Jet Propulsion Laboratory, Institut Systèmes Intelligents et de Robotique, Centre National de la Recherche Scientifique

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago