Papers

2

Total Citations

116

H-Index

2

About

Peter Sutor’s research sits at the intersection of robotics, neuromorphic computing, and embodied intelligence, with a particular focus on how machines can learn to seamlessly integrate perception with action. His most influential work, “Learning sensorimotor control with neuromorphic sensors: Toward hyperdimensional active perception” (2019, 112 citations), challenges the traditional separation between sensing and movement in robotics. Sutor proposes a framework where sensorimotor control is learned directly from neuromorphic sensor data, enabling robots to fuse perception with motoric ability in a unified, hyperdimensional space—a key step toward truly active perception. This work has become a touchstone for researchers exploring bio-inspired, energy-efficient robotic systems. Beyond his technical contributions, Sutor is also a dedicated educator and interdisciplinary advocate. In his paper “Performing robots” (2013), he demonstrates how engaging students in creative, cross-disciplinary projects—blending robotics with performance—can foster innovation, critical thinking, and problem-solving skills. Through this work, he champions a culture of hands-on, undergraduate research that bridges engineering and the arts, inspiring a new generation of roboticists to think beyond traditional boundaries.

Research Focus

Key Achievements

2
H-Index
2
Papers
116
Total Citations
58
Avg Citations/Paper
🏆 Most Cited Paper
Learning sensorimotor control with neuromorphic sensors: Toward hyperdimensional active perception
112 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of Maryland, College Park, Pennsylvania State University

Top Papers

  1. 1
  2. 2
    Performing robots
    4 citations · 2013

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago