3 papers
cs.RO2025
Beyond Egocentric Limits: Multi-View Depth-Based Learning for Robust Quadrupedal Locomotion
Rémy Rahem, Wael Suleiman
Recent progress in legged locomotion has allowed highly dynamic and parkour-like behaviors for robots, similar to their biological counterparts. Yet, these methods mostly rely on e…
cs.RO2025
Enhancing Path Planning Performance through Image Representation Learning of High-Dimensional Configuration Spaces
Jorge Ocampo Jimenez, Wael Suleiman
This paper presents a novel method for accelerating path-planning tasks in unknown scenes with obstacles by utilizing Wasserstein Generative Adversarial Networks (WGANs) with Gradi…
cs.RO2024
Visualizing High-Dimensional Configuration Spaces: A Comprehensive Analytical Approach
Jorge Ocampo Jimenez, Wael Suleiman
The representation of a Configuration Space C plays a vital role in accelerating the finding of a collision-free path for sampling-based motion planners where the majority of compu…