Mamoru Tanaka

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About

Mamoru Tanaka is a pioneering researcher in bio-inspired analog computing and robotic path planning, whose work bridges neuromorphic engineering and autonomous navigation. His key research areas include resistive network-based computation, cellular neural networks, and parallel path-searching algorithms for multi-robot systems. Tanaka’s major contributions lie in developing novel analog dynamics approaches that mimic retinal information processing to solve complex spatial problems. His most cited work, “Shortest path searching for robot walking using an analog resistive network” (2002, 20 citations), introduced a local current comparison method that enables efficient pathfinding through analog resistive meshes, demonstrating how biological principles can inspire robotic locomotion. In “A resistive mesh analysis method for parallel path searching” (2002, 13 citations), he proposed a constructive parallel method using unity resistive meshes to solve Poisson equation-based fields, including a bottleneck detection approach. His earlier work on “Path planning method for multi-robots using a cellular neural network” (1998, 6 citations) integrated resistive grids with competitive and digital networks for coordinated multi-agent navigation. Tanaka’s research has been foundational in demonstrating how analog computational primitives can achieve efficient, parallel solutions to robotic path planning problems, influencing subsequent work in neuromorphic robotics and distributed control systems.