7 citations · 7 across the 4 of their papers we have counts for
6 papers
FDTD Model of Noise Pollution from an AI Data Center
Gavin Buxton
The sudden growth in AI data centers is raising numerous environmental concerns. Low-frequency noise pollution is a concern for local residents, that may not just be an annoyance b…
Robust Convex Model Predictive Control with collision avoidance guarantees for robot manipulators
Bernhard Wullt, Johannes Köhler, Per Mattsson +2
Industrial manipulators typically operate in cluttered environments, where safe motion planning is critical. However, model uncertainties further complicate this task, which leads…
A neural signed configuration distance function for path planning of picking manipulators
Bernhard Wullt, Mikael Norrlöf, Per Mattsson +1
Picking manipulators are task specific robots, with fewer degrees of freedom compared to general-purpose manipulators, and are heavily used in industry. The efficiency of the picki…
On the equivalence of direct and indirect data-driven predictive control approaches
Per Mattsson, Fabio Bonassi, Valentina Breschi +1
Recently, several direct Data-Driven Predictive Control (DDPC) methods have been proposed, advocating the possibility of designing predictive controllers from historical input-outp…
Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning
Ruoqi Zhang, Ziwei Luo, Jens Sjölund +2
This paper presents advanced techniques of training diffusion policies for offline reinforcement learning (RL). At the core is a mean-reverting stochastic differential equation (SD…
Structured state-space models are deep Wiener models
Fabio Bonassi, Carl Andersson, Per Mattsson +1
The goal of this paper is to provide a system identification-friendly introduction to the Structured State-space Models (SSMs). These models have become recently popular in the mac…