45 citations · 106 across the 35 of their papers we have counts for
6 papers · 1 filter
ExoRecovery: Push Recovery with a Lower-Limb Exoskeleton based on Stepping Strategy
Zeynep Özge Orhan, Milad Shafiee, Vincent Juillard +3
Balance loss is a significant challenge in lower-limb exoskeleton applications, as it can lead to potential falls, thereby impacting user safety and confidence. We introduce a cont…
Maximizing Performance with Minimal Resources for Real-Time Transition Detection
Zeynep Ozge Orhan, Andrea Dal Prete, Anastasia Bolotnikova +3
Assistive devices, such as exoskeletons and prostheses, have revolutionized the field of rehabilitation and mobility assistance. Efficiently detecting transitions between different…
ManyQuadrupeds: Learning a Single Locomotion Policy for Diverse Quadruped Robots
Milad Shafiee, Guillaume Bellegarda, Auke Ijspeert
Learning a locomotion policy for quadruped robots has traditionally been constrained to a specific robot morphology, mass, and size. The learning process must usually be repeated f…
Identifying Important Sensory Feedback for Learning Locomotion Skills
Wanming Yu, Chuanyu Yang, Christopher McGreavy +5
Robot motor skills can be learned through deep reinforcement learning (DRL) by neural networks as state-action mappings. While the selection of state observations is crucial, there…
DeepTransition: Viability Leads to the Emergence of Gait Transitions in Learning Anticipatory Quadrupedal Locomotion Skills
Milad Shafiee, Guillaume Bellegarda, Auke Ijspeert
Quadruped animals seamlessly transition between gaits as they change locomotion speeds. While the most widely accepted explanation for gait transitions is energy efficiency, there…
Puppeteer and Marionette: Learning Anticipatory Quadrupedal Locomotion Based on Interactions of a Central Pattern Generator and Supraspinal Drive
Milad Shafiee, Guillaume Bellegarda, Auke Ijspeert
Quadruped animal locomotion emerges from the interactions between the spinal central pattern generator (CPG), sensory feedback, and supraspinal drive signals from the brain. Comput…