Papers

6

Total Citations

39

H-Index

3

About

Adam Pettinger is a robotics researcher focused on enabling robots to perform complex physical tasks with greater autonomy and reliability. His work centers on **affordance modeling**, **compliant manipulation**, and **constrained motion planning**—critical for robots operating in uncertain or remote environments, from industrial settings to space. Pettinger’s most influential contribution is the development of **Affordance Primitives**, a framework that uses screw theory to model how a robot can interact with objects, reducing the cognitive burden on human teleoperators. His 2020 paper on this topic has garnered **14 citations**, establishing a foundation for supervised autonomy in contact tasks. He also introduced the **Generalized Contact Control Framework (GCCF)** for integrating active and passive compliance, enabling robots to complete tasks despite environmental uncertainty. Notably, Pettinger designed a **passive tool changer** for elastic manipulators, advancing multi-tool autonomy. His latest work includes the **Robotic Space Simulator (RSS)**, a dual-Gough-Stewart platform testbed for in-space robotic operations, and a novel method for **direct sampling of screw-constraint manifolds** to efficiently plan motions for articulated objects. With over **39 total citations** and a trajectory toward space robotics, Pettinger is shaping how robots handle contact-rich tasks in the real world.

Research Focus

Key Achievements

3
H-Index
6
Papers
39
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Reducing the Teleoperator’s Cognitive Burden for Complex Contact Tasks Using Affordance Primitives
14 citations · 2020
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Walker (United States), The University of Texas at Austin, Texas A&M University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago