Peter Eggenberger Hotz
Information Technology University, University of Zurich, University of Southern Denmark, Maersk (Denmark)
Papers
8
Total Citations
150
H-Index
6
About
Peter Eggenberger Hotz is a pioneer in developmental and evolutionary robotics, whose work bridges artificial intelligence, biomechanics, and paleontology. His research centers on creating adaptive neural controllers inspired by biological development, particularly through "embryogenic evolution"—a method that allows neural networks to grow, learn, and adapt dynamically. A key contribution is the polymorphic central pattern generator (CPG) circuit for bipedal locomotion, which uses neuromodulation to enable agile, adaptive walking in robots (50 citations). He also demonstrated how simulated development—progressively increasing sensory and motor complexity—can improve robotic learning, as shown in his work with a robotic hand-arm-eyes system (22 citations). Notably, Eggenberger Hotz extended embodied AI to paleontology, designing actuated bivalve robots to study burrowing locomotion in sediment, offering new insights into ancient life (17 citations). His "ligand-receptor" concept for adaptive neural control of tendon-driven hands (7 citations) further showcases his impact. With over 150 total citations, his work continues to inspire researchers exploring the intersection of evolution, development, and robotics.
Research Focus
Key Achievements
Top Papers
- 1Neuromodulated Control of Bipedal Locomotion Using a Polymorphic CPG Circuit50 citations · 2003
- 2
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- 4Actuated bivalve robot study of the burrowing locomotion in sediment17 citations · 2010
- 5Artificial Bivalves – The Biomimetics of Underwater Burrowing9 citations · 2011
- 6An adaptive neural controller for a tendon driven robotic hand.7 citations · 2006
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