41 citations · 44 across the 8 of their papers we have counts for
10 papers
Bicycle Acrobatics with Reinforcement Learning
Shamel Fahmi, Arianna Ilvonen, Samuel Zapolsky +8
Bicycle robots are fast and energy efficient, but their simple mechanical design and their underactuated and non-holonomic dynamics make highly agile maneuvers difficult to achieve…
LineRides: Line-Guided Reinforcement Learning for Bicycle Robot Stunts
Seungeun Rho, Shamel Fahmi, Jeonghwan Kim +3
Designing reward functions for agile robotic maneuvers in reinforcement learning remains difficult, and demonstration-based approaches often require reference motions that are unav…
Flip Stunts on Bicycle Robots using Iterative Motion Imitation
Jeonghwan Kim, Shamel Fahmi, Seungeun Rho +2
This work demonstrates a front-flip on bicycle robots via reinforcement learning, particularly by imitating reference motions that are infeasible and imperfect. To address this, we…
System Design of the Ultra Mobility Vehicle: A Driving, Balancing, and Jumping Bicycle Robot
Benjamin Bokser, Daniel Gonzalez, Aaron Preston +39
Trials cyclists and mountain bike riders can hop, jump, balance, and drive on one or both wheels. This versatility allows them to achieve speed and energy-efficiency on smooth terr…
Reinforcement Learning for Legged Robots: Motion Imitation from Model-Based Optimal Control
AJ Miller, Shamel Fahmi, Matthew Chignoli +1
We propose MIMOC: Motion Imitation from Model-Based Optimal Control. MIMOC is a Reinforcement Learning (RL) controller that learns agile locomotion by imitating reference trajector…
ViTAL: Vision-Based Terrain-Aware Locomotion for Legged Robots
Shamel Fahmi, Victor Barasuol, Domingo Esteban +2
This work is on vision-based planning strategies for legged robots that separate locomotion planning into foothold selection and pose adaptation. Current pose adaptation strategies…
On Terrain-Aware Locomotion for Legged Robots
Shamel Fahmi
(Simplified Abstract) To accomplish breakthroughs in dynamic whole-body locomotion, legged robots have to be terrain aware. Terrain-Aware Locomotion (TAL) implies that the robot ca…
On State Estimation for Legged Locomotion over Soft Terrain
Shamel Fahmi, Geoff Fink, Claudio Semini
Locomotion over soft terrain remains a challenging problem for legged robots. Most of the work done on state estimation for legged robots is designed for rigid contacts, and does n…
STANCE: Locomotion Adaptation over Soft Terrain
Shamel Fahmi, Michele Focchi, Andreea Radulescu +3
Whole-body Control (WBC) has emerged as an important framework in locomotion control for legged robots. However, most of WBC frameworks fail to generalize beyond rigid terrains. Le…
Passive Whole-body Control for Quadruped Robots: Experimental Validation over Challenging Terrain
Shamel Fahmi, Carlos Mastalli, Michele Focchi +1
We present experimental results using a passive whole-body control approach for quadruped robots that achieves dynamic locomotion while compliantly balancing the robot's trunk. We…