Robert Skilton — accepted AI-conference papers

2026

Scalable Solution Methods for Dec-POMDPs with Deterministic Dynamics

Yang You, Alex Schutz, Zhikun Li, Bruno Lacerda, Robert Skilton, Nick Hawes

AAAI 2026technical

Many high-level multi-agent planning problems, such as multi-robot navigation and path planning, can be modeled with deterministic actions and observations. In this work, we focus on such domains and introduce the class of Deterministic Decentralized POMDPs (Det-Dec-POMDPs)—a subclass of Dec-POMDPs

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2025

A Kinematics Optimization Framework with Improved Computational Efficiency for Task-Based Optimum Design of Serial Manipulators in Cluttered Environments

Nikola Petkov, Ozan Tokatli, Kaiqiang Zhang, Huapeng Wu, Robert Skilton

ICRA 2025

It is challenging to find optimum kinematic designs for non-standard robotic manipulators, e.g., medical, nuclear, and space manipulators, which are demanded to adapt to arbitrary complex tasks in constraints. Such design optimization can be modelled as a multi-dimensional non-convex optimization pr

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