Hello! My name is Guillaume Sartoretti, and I was a Postdoctoral Fellow in the Robotics Institute at Carnegie Mellon University. My research focuses on the distributed/decentralized coordination of numerous agents, at the interface between conventional control and artificial intelligence. Applications range from multi-robot systems, where independent robots need to coordinate their actions to achieve a common goal, to high-DoF articulated robots, where joints need to be carefully coupled during locomotion in rough terrain.
I have started my new faculty position at the National University of Singapore. This website will no longer be updated, but you can find information about this new chapter of my career on my
Joint-Space inertial CPG with full SE(3) body pose control for locomotion, climbing, and payload balancing on stairs, steep inclines, unstructured terrain, etc.
Task-Space Central Pattern Generator for a legged robot (hexapod) locomoting while carrying a fixed camera, where gaze control and locomotion must be controlled independently.
Multi-agent path finding in complex environments, using either conventional decentralized planning or distributed-RL based approaches.
Multi-robot search of an area by a team of heterogeneous platforms, by leveraging the different capabilities of the robots.
Let’s train multiple simple robots (green) to gather and assemble simple block elements (brown, obtained from pink sources) to build complex 3D structures!
Training a snake robot to slither through unstructured environment, via distributed reinforcement learning.
Joint-Space Central Pattern Generator for the locomotion of a legged robot in challenging environments (stairs, steep inclines, unstructured terrain, etc.).