6 citations · 6 across the 4 of their papers we have counts for
4 papers · 1 filter
Optimizing Trajectory-Trees in Belief Space: An Application from Model Predictive Control to Task and Motion Planning
Camille Phiquepal, Marc Toussaint
This paper explores the benefits of computing arborescent trajectories (trajectory-trees) instead of commonly used sequential trajectories for partially observable robotic planning…
Asymptotically Optimal Belief Space Planning in Discrete Partially-Observable Domains
Janis Eric Freund, Camille Phiquepal, Andreas Orthey +1
Robots often have to operate in discrete partially observable worlds, where the states of world are only observable at runtime. To react to different world states, robots need cont…
Control-Tree Optimization: an approach to MPC under discrete Partial Observability
Camille Phiquepal, Marc Toussaint
This paper presents a new approach to Model Predictive Control for environments where essential, discrete variables are partially observed. Under this assumption, the belief state…
Path-Tree Optimization in Discrete Partially Observable Environments using Rapidly-Exploring Belief-Space Graphs
Camille Phiquepal, Andreas Orthey, Nicolas Viennot +1
Robots often need to solve path planning problems where essential and discrete aspects of the environment are partially observable. This introduces a multi-modality, where the robo…