70 citations · 157 across the 20 of their papers we have counts for
18 papers · 1 filter
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…
Parallel and Proximal Constrained Linear-Quadratic Methods for Real-Time Nonlinear MPC
Wilson Jallet, Ewen Dantec, Etienne Arlaud +2
Recent strides in nonlinear model predictive control (NMPC) underscore a dependence on numerical advancements to efficiently and accurately solve large-scale problems. Given the su…
From Compliant to Rigid Contact Simulation: a Unified and Efficient Approach
Justin Carpentier, Louis Montaut, Quentin Le Lidec
Whether rigid or compliant, contact interactions are inherent to robot motions, enabling them to move or manipulate things. Contact interactions result from complex physical phenom…
Risk-Sensitive Extended Kalman Filter
Armand Jordana, Avadesh Meduri, Etienne Arlaud +2
In robotics, designing robust algorithms in the face of estimation uncertainty is a challenging task. Indeed, controllers often do not consider the estimation uncertainty and only…
Contact Models in Robotics: a Comparative Analysis
Quentin Le Lidec, Wilson Jallet, Louis Montaut +3
Physics simulation is ubiquitous in robotics. Whether in model-based approaches (e.g., trajectory optimization), or model-free algorithms (e.g., reinforcement learning), physics si…
Constrained Differential Dynamic Programming: A primal-dual augmented Lagrangian approach
Wilson Jallet, Antoine Bambade, Nicolas Mansard +1
Trajectory optimization is an efficient approach for solving optimal control problems for complex robotic systems. It relies on two key components: first the transcription into a s…