13 citations · 21 across the 4 of their papers we have counts for
4 papers
Planning and Inverse Kinematics of Hyper-Redundant Manipulators with VO-FABRIK
Cristian Morasso, Daniele Meli, Yann Divet +2
Hyper-redundant Robotic Manipulators (HRMs) offer great dexterity and flexibility of operation, but solving Inverse Kinematics (IK) is challenging. In this work, we introduce VO-FA…
Learning Logic Specifications for Policy Guidance in POMDPs: an Inductive Logic Programming Approach
Daniele Meli, Alberto Castellini, Alessandro Farinelli
Partially Observable Markov Decision Processes (POMDPs) are a powerful framework for planning under uncertainty. They allow to model state uncertainty as a belief probability distr…
Learning Logic Specifications for Soft Policy Guidance in POMCP
Giulio Mazzi, Daniele Meli, Alberto Castellini +1
Partially Observable Monte Carlo Planning (POMCP) is an efficient solver for Partially Observable Markov Decision Processes (POMDPs). It allows scaling to large state spaces by com…
Logic programming for deliberative robotic task planning
Daniele Meli, Hirenkumar Nakawala, Paolo Fiorini
Over the last decade, the use of robots in production and daily life has increased. With increasingly complex tasks and interaction in different environments including humans, robo…