Robot Motor Intelligence (RoMI) Lab - Heriot-Watt University
Description: Carlos Mastalli is a robotics researcher focused on multi-contact planning and control for legged robots. He is main motivation is to enable robots (e.g. HyQ, HRP-2, Talos, Atlas) to move everywhere by combining optimal control and machine learning.
Optimal Control - Motion Planning - Trajectory Optimization Reinforcement Learning - Machine Learning - Legged Robots
I am a robotics researcher working in the intersection of model predictive control and machine learning for motor control in legged robots. The aim of my research is to enable robots to move everywhere. In particular, I am focused on the problem of loco-manipulation tasks since it combines the main challenges in robot mobility. My research combines the formalism of model-base approach with the exploration of vast robot’s data.
I completed my PhD on “ Planning and Execution of Dynamic Whole-Body Locomotion on Challenging Terrain ” in April 2017 in the Dynamic Legged System lab at Istituto Italiano di Tecnologia. After that, I served as Research Fellow from April to December 2017. During this period, I mainly contributed to planning, perception and control framework for legged locomotion on challenging terrain. I also designed a considerably part of the HyQ’s software framework. In my career, I have spent fruitful time in different
Robot Motor Intelligence (RoMI) Lab - Heriot-Watt University