Papers
30
Total Citations
542
H-Index
12
About
Malte Schilling is a prominent researcher at the intersection of computational neuroscience, bio-inspired robotics, and autonomous locomotion control. His work focuses on decentralized neural control architectures for hexapod walking systems, drawing inspiration from the biomechanics and neuroscience of stick insects to develop adaptive robotic platforms. Schilling's most celebrated contribution is the Walknet framework — a biologically inspired neural network controller that replicates an impressive breadth of walking and standing behaviors observed in insects, validated through kinematic simulations and physical six-legged robots (168 citations). He has consistently championed decentralized control philosophies, demonstrating that complex multi-legged coordination can emerge without centralized body models or explicit kinematic computation, as illustrated in his positive velocity feedback work and his 2020 neural network model of insect walking (62 citations). His integrative biomimetics research (53 citations) further bridges neuroscience and engineering by synthesizing disparate fields into coherent locomotion systems, exemplified by compliant robots like HECTOR. More recently, Schilling has explored hierarchical deep reinforcement learning as a pathway to more adaptive decentralized control. With over 400 cumulative citations, his research has meaningfully advanced our understanding of how biological principles can inspire robust, flexible autonomous robots capable of navigating unpredictable real-world terrain.
Research Focus
Key Achievements
Top Papers
- 1Walknet, a bio-inspired controller for hexapod walking168 citations · 2013
- 2
- 3Integrative Biomimetics of Autonomous Hexapedal Locomotion53 citations · 2019
- 4
- 5
- 6HECTOR, A Bio-Inspired and Compliant Hexapod Robot24 citations · 2014
- 7
- 8
- 9Hierarchical MMC Networks as a manipulable body model18 citations · 2007
- 10