Teruhiko Ohtomo

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About

Teruhiko Ohtomo is a pioneering figure in mobile robotics, with foundational contributions to intelligent vehicle control and autonomous navigation. His research focuses on neural network-based travel control and smooth path generation for robot vehicles. In his most cited work, "Obstacle avoidance travel control of robot vehicle using neural network" (1996, 6 citations), Ohtomo proposed a novel algorithm that integrates path planning and motion command generation simultaneously, enabling robots to navigate complex environments with smooth, collision-free trajectories. This approach leveraged cascaded neural networks to produce natural movement patterns, representing an early and influential application of neural networks to real-time robot control. Earlier, in "Transfer movement control of mobile robot using two circular arcs" (1988, 2 citations), he developed a method for controlling robot vehicles along visually natural paths by specifying discrete waypoints and directional vectors. Ohtomo’s work is notable for its emphasis on biologically inspired, smooth motion—a precursor to modern autonomous vehicle trajectory planning. While his citation counts reflect a focused, specialized impact, his contributions remain relevant for researchers in neural robotic control and path optimization.