20 citations · 85 across the 21 of their papers we have counts for
7 papers · 1 filter
Load-Based Variable Transmission Mechanism for Robotic Applications
Sinan Emre, Victor Barasuol, Matteo Villa +1
This paper presents a Load-Based Variable Transmission (LBVT) mechanism designed to enhance robotic actuation by dynamically adjusting the transmission ratio in response to externa…
Load-bearing Assessment for Safe Locomotion of Quadruped Robots on Collapsing Terrain
Vivian S. Medeiros, Giovanni B. Dessy, Thiago Boaventura +3
Collapsing terrains, often present in search and rescue missions or planetary exploration, pose significant challenges for quadruped robots. This paper introduces a robust locomoti…
Proprioceptive Image: An Image Representation of Proprioceptive Data from Quadruped Robots for Contact Estimation Learning
Gabriel Fischer Abati, João Carlos Virgolino Soares, Giulio Turrisi +2
This paper presents a novel approach for representing proprioceptive time-series data from quadruped robots as structured two-dimensional images, enabling the use of convolutional…
CroSTAta: Cross-State Transition Attention Transformer for Robotic Manipulation
Giovanni Minelli, Giulio Turrisi, Victor Barasuol +1
Learning robotic manipulation policies through supervised learning from demonstrations remains challenging when policies encounter execution variations not explicitly covered durin…
RAKOMO: Reachability-Aware K-Order Markov Path Optimization for Quadrupedal Loco-Manipulation
Mattia Risiglione, Abdelrahman Abdalla, Victor Barasuol +3
Legged manipulators, such as quadrupeds equipped with robotic arms, require motion planning techniques that account for their complex kinematic constraints in order to perform mani…
Guided Reinforcement Learning for Omnidirectional 3D Jumping in Quadruped Robots
Riccardo Bussola, Michele Focchi, Giulio Turrisi +2
Jumping poses a significant challenge for quadruped robots, despite being crucial for many operational scenarios. While optimisation methods exist for controlling such motions, the…
Primal-Dual iLQR for GPU-Accelerated Learning and Control in Legged Robots
Lorenzo Amatucci, João Sousa-Pinto, Giulio Turrisi +3
This paper introduces a novel Model Predictive Control (MPC) implementation for legged robot locomotion that leverages GPU parallelization. Our approach enables both temporal and s…