6 citations · 11 across the 14 of their papers we have counts for
14 papers
SATA: Safe and Adaptive Torque-Based Locomotion Policies Inspired by Animal Learning
Peizhuo Li, Hongyi Li, Ge Sun +7
Despite recent advances in learning-based controllers for legged robots, deployments in human-centric environments remain limited by safety concerns. Most of these approaches use p…
Surena-V: A Humanoid Robot for Human-Robot Collaboration with Optimization-based Control Architecture
Mohammad Ali Bazrafshani, Aghil Yousefi-Koma, Amin Amani +10
This paper presents Surena-V, a humanoid robot designed to enhance human-robot collaboration capabilities. The robot features a range of sensors, including barometric tactile senso…
AllGaits: Learning All Quadruped Gaits and Transitions
Guillaume Bellegarda, Milad Shafiee, Auke Ijspeert
We present a framework for learning a single policy capable of producing all quadruped gaits and transitions. The framework consists of a policy trained with deep reinforcement lea…
Online Optimization of Central Pattern Generators for Quadruped Locomotion
Zewei Zhang, Guillaume Bellegarda, Milad Shafiee +1
Typical legged locomotion controllers are designed or trained offline. This is in contrast to many animals, which are able to locomote at birth, and rapidly improve their locomotio…
Learning-based Hierarchical Control: Emulating the Central Nervous System for Bio-Inspired Legged Robot Locomotion
Ge Sun, Milad Shafiee, Peizhuo Li +3
Animals possess a remarkable ability to navigate challenging terrains, achieved through the interplay of various pathways between the brain, central pattern generators (CPGs) in th…
Quadruped-Frog: Rapid Online Optimization of Continuous Quadruped Jumping
Guillaume Bellegarda, Milad Shafiee, Merih Ekin Özberk +1
Legged robots are becoming increasingly agile in exhibiting dynamic behaviors such as running and jumping. Usually, such behaviors are either optimized and engineered offline (i.e.…
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…
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…
Online Bipedal Locomotion Adaptation for Stepping on Obstacles Using a Novel Foot Sensor
Pezhman Abdolahnezhad, Aghil Yousefi-Koma, Amirhosein Vedadi +3
In this paper, we present a novel control architecture for the online adaptation of bipedal locomotion on inclined obstacles. In particular, we introduce a novel, cost-effective, a…
Visual CPG-RL: Learning Central Pattern Generators for Visually-Guided Quadruped Locomotion
Guillaume Bellegarda, Milad Shafiee, Auke Ijspeert
We present a framework for learning visually-guided quadruped locomotion by integrating exteroceptive sensing and central pattern generators (CPGs), i.e. systems of coupled oscilla…
Online DCM Trajectory Generation for Push Recovery of Torque-Controlled Humanoid Robots
Milad Shafiee, Giulio Romualdi, Stefano Dafarra +2
We present a computationally efficient method for online planning of bipedal walking trajectories with push recovery. In particular, the proposed methodology fits control architect…