Michel Alsaba
Papers
2
Total Citations
8
H-Index
2
About
Dr. Michel Alsaba is a robotics researcher specializing in bio-inspired locomotion and intelligent control for multi-legged robots. His work sits at the intersection of machine learning and dynamic systems, with a focus on enabling stable, adaptive movement in complex environments. Dr. Alsaba’s major contributions include the development of a novel Central Pattern Generator (CPG)-based control methodology that achieves smooth gait transitions for hexapod robots. By modifying the Phase Oscillator within the CPG network, his approach allows a robot to seamlessly shift between different gaits—such as from a tripod to a wave gait—without destabilizing its motion, a critical challenge in legged robotics. Additionally, he has pioneered the use of Long Short-Term Memory (LSTM) networks to estimate the state of a mobile robot’s legs, leveraging deep learning for real-time proprioceptive feedback. Though early in his career, his work has already garnered attention, with his 2024 papers accumulating 5 and 3 citations respectively. These contributions are foundational for advancing the autonomy and agility of field robots, with potential applications in search-and-rescue and planetary exploration.
Research Focus
Key Achievements
Top Papers
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- 2