8 papers
Coupled Local and Global World Models for Efficient First Order RL
Joseph Amigo, Rooholla Khorrambakht, Nicolas Mansard +1
World models offer a promising avenue for more faithfully capturing complex dynamics, including contacts and non-rigidity, as well as complex sensory information, such as visual pe…
Cooptimizing Safety and Performance Using Safety Value-Constrained Model Predictive Control
Hao Wang, Nam Nguyen, Armand Jordana +2
Autonomous systems are increasingly deployed in real-world environments, where they must achieve high performance while maintaining safety under state and input constraints. Althou…
Hippo: High-performance Interior-Point and Projection-based Solver for Generic Constrained Trajectory Optimization
Haizhou Zhao, Ludovic Righetti, Majid Khadiv
Trajectory optimization is the core of modern model-based robotic control and motion planning. Existing trajectory optimizers, based on sequential quadratic programming (SQP) or di…
WorldPlanner: Monte Carlo Tree Search and MPC with Action-Conditioned Visual World Models
R. Khorrambakht, Joaquim Ortiz-Haro, Joseph Amigo +4
Robots must understand their environment from raw sensory inputs and reason about the consequences of their actions in it to solve complex tasks. Behavior Cloning (BC) leverages ta…
Infinite-Horizon Value Function Approximation for Model Predictive Control
Armand Jordana, Sébastien Kleff, Arthur Haffemayer +4
Model Predictive Control has emerged as a popular tool for robots to generate complex motions. However, the real-time requirement has limited the use of hard constraints and large…
An Introduction to Zero-Order Optimization Techniques for Robotics
Armand Jordana, Jianghan Zhang, Joseph Amigo +1
Zero-order optimization techniques are becoming increasingly popular in robotics due to their ability to handle non-differentiable functions and escape local minima. These advantag…