Ross Hartley

University of Michigan–Ann Arbor

Papers

12

Total Citations

839

H-Index

9

About

Ross Hartley is a leading researcher in legged robotics, specializing in state estimation, feedback control, and dynamic locomotion for bipedal systems. His most impactful contribution is the development of contact-aided invariant extended Kalman filtering (InEKF), a groundbreaking approach that fuses inertial, kinematic, and contact data to achieve robust robot state estimation without relying on vision—a method that has garnered over 295 citations. Hartley’s work on the Cassie bipedal robot, including feedback control for walking, standing, and even riding a Segway (216 citations), has provided the robotics community with a standardized platform for advancing locomotion algorithms. He has also pioneered the use of supervised learning to stabilize underactuated bipedal walking (60 citations) and introduced hybrid contact preintegration for visual-inertial-contact state estimation using factor graphs (54 citations). His research bridges theory and practice, enabling stable, high-speed walking in real-world environments, including outdoor terrain. With over 800 total citations across his top papers, Hartley’s innovations in nonlinear observer design and gait libraries have become foundational for modern legged robot autonomy.

Research Focus

Key Achievements

9
H-Index
12
Papers
839
Total Citations
70
Avg Citations/Paper
🏆 Most Cited Paper
Contact-aided invariant extended Kalman filtering for robot state estimation
295 citations · 2020
📈 Most Prolific Year: 2018 (5 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: University of Michigan–Ann Arbor

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago