About

Kris Hauser is a prominent robotics researcher whose work spans motion planning, humanoid locomotion, robotic manipulation, and surgical simulation. His contributions have fundamentally advanced how robots navigate complex environments and interact with the physical world. Hauser's early work on legged and humanoid robots broke new ground by developing non-gaited planners capable of handling unpredictable, uneven terrain — allowing robots to use hands, knees, and feet in flexible combinations rather than relying on rigid walking gaits (206 and 114 citations). His multi-modal motion planning framework further enabled robots to reason simultaneously over discrete contact states and continuous motion, a critical advance for dexterous manipulation (145 citations). On the algorithmic side, Hauser's lazy collision-checking planners dramatically improved the efficiency of asymptotically-optimal sampling-based methods, addressing a longstanding bottleneck in practical deployment (162 citations). His trajectory smoothing work similarly made manipulator motion faster and more physically executable (108 citations). Beyond robotics, Hauser made notable contributions to surgical simulation, developing real-time needle insertion algorithms relevant to biopsies and neurosurgery (156 citations). His leadership in analyzing the landmark Amazon Picking Challenge (425 citations) helped define open problems in warehouse automation. Collectively, his research has accumulated over 1,600 citations, reflecting broad and lasting influence across robotics and human-robot interaction.

Research Focus

Key Achievements

32
H-Index
105
Papers
3,701
Total Citations
35
Avg Citations/Paper
🏆 Most Cited Paper
Analysis and Observations From the First Amazon Picking Challenge
425 citations · 2016
📈 Most Prolific Year: 2020 (9 Papers)
🤝 Key Collaborators: 196
🏛 Institutions: Duke University, Stanford University, University of California, Berkeley, Indiana University Bloomington, Indiana University, Laboratoire d'Informatique de Paris-Nord

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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