1 citations · 1 across the 11 of their papers we have counts for
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Task-Space Motion-Force Nonlinear Model Predictive Control for Precise and Compliant Control under Uncertainties
Quang-Nam Nguyen, Ludovic Righetti
In Nonlinear Model Predictive Control (NMPC), the control law is implicitly determined by the solution of an Optimal Control Problem (OCP). Consequently, OCP design is often tailor…
FLEX-WAM: Flexible Block-Causal World-Action Models for Long-Horizon Imagination and Planning
R. Khorrambakht, Joseph Amigo, Félix Lebel +4
World--action models (WAMs) promise a unified model that predicts action-conditioned futures, generates feasible actions, and supports planning in imagination. However, existing jo…
VAMPS: Visual and Motor Policies from Sampling-Based Planning
Mohamed Yassine Kabouri, Pietro Noah Crestaz, Quang-Nam Nguyen +3
Learning robot policies directly on physical systems remains difficult because data collection is costly and policy exploration can be unsafe. We introduce Visual and Motor Policie…
CollisionSplatting: Collision-Aware Motion Planning in 3DGS Scenes with Image-Conditioned Objectives and Adjustable Conservatism
R. Khorrambakht, Joaquim Ortiz-Haro, Stephan Weiss +1
Incorporating dense visual information into motion planning remains challenging, as geometric planners rely on abstracted scene representations that discard visual richness, while…
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…
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…