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About

Filipp Seljanko is a robotics researcher whose work focuses on legged locomotion, gait generation, and autonomous fault recovery for walking robots, particularly hexapod platforms designed for urban search and rescue (USAR) operations. His most cited paper (23 citations) introduces a hybrid genetic-gravitational algorithm that combines the Gravitational Search Algorithm with genetic operators to efficiently generate hexapod gaits, demonstrating a novel approach to optimization in robotics. Seljanko also proposed an omnidirectional locomotion strategy using virtual leading edges, enabling multi-legged robots to maneuver more flexibly—a concept he later extended to recovery from leg loss incidents, allowing a robot to reconfigure its gait and continue operating after damage. His work on low-cost electronic architectures and fault detection algorithms, including the use of panoramic catadioptric imaging for real-time monitoring, directly addresses the practical constraints of deploying robots in disaster scenarios. With contributions spanning gait generation, fault tolerance, and USAR-specific design, Seljanko’s research advances the reliability and adaptability of legged robots in challenging, real-world environments.