A biologically inspired neural net for trajectory formation and obstacle avoidance

DOI10.1007/BF00209422zbMath0849.92003OpenAlexW1967468731MaRDI QIDQ1916518

Andrzej Komoda, Stan C. A. M. Gielen, Roy Glasius

Publication date: 8 July 1996

Published in: Biological Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00209422

zbMATH Keywords

obstacle avoidancemotor mapanalog neuronsfeedforward connectionssensory maptopographically ordered neural mapstrajectory formationtwo-layered neural network

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20)

Related Items (3)

The dynamic wave expansion neural network model for robot motion planning in time-varying environments ⋮ Neural network approach to collision free path-planning for robotic manipulators ⋮ Self-organized formation of a set of scaling filters and their neighbouring connections

Cites Work

• On the Piano Movers problem. II: General techniques for computing topological properties of real algebraic manifolds
• Self-organized formation of topologically correct feature maps
• Robot motion planning with uncertainty in control and sensing
• Dynamics of pattern formation in lateral-inhibition type neural fields
• Saccadic motor planning by integrating visual information and pre-information on neural dynamic fields
• Spatial Planning: A Configuration Space Approach
• Neurons with graded response have collective computational properties like those of two-state neurons.

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