Papers

4

Total Citations

67

H-Index

4

About

Allison Thackston is a leading researcher in robotics, with a focus on enabling intelligent, autonomous behavior in complex environments. Her work bridges the critical gap between low-level motor control and high-level symbolic planning, a key challenge for generalist robots. Thackston’s major contributions include developing methods for learning symbolic representations that allow robots to sequence parameterized skills for goal-directed planning, a foundational capability for long-horizon tasks. Her research on the Robonaut 2 humanoid robot, including model-based dynamic motion control and the pioneering use of the Robot Operating System (ROS) in space, has been instrumental in advancing dexterous manipulation on the International Space Station. With over 67 combined citations across her most influential papers, her work on multi-step mobile manipulation architectures further demonstrates her impact in creating integrated systems for real-world applications. Thackston’s achievements highlight her role in pushing the boundaries of what robots can achieve in both terrestrial and extraterrestrial settings.

Research Focus

Key Achievements

4
H-Index
4
Papers
67
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Learning Symbolic Representations for Planning with Parameterized Skills
25 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 19
🏛 Institutions: Toyota Research Institute, Oceaneering International (United States), Toyota Motor Corporation (United States)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago