activity
20162026
most citedEmbedded nonlinear model predictive control for obstacle avoidance using PANOC

100 citations · 335 across the 27 of their papers we have counts for

collaborators

35 papers

math.OC2026

Sampled-data optimal control of linear fractional-order systems

Pantelis Sopasakis

This paper studies the problem of optimal control of Caputo linear fractional-order systems of order with continuous-time state constraints and input constraints. The…

eess.SY2026

Multi-Agent Temporal Logic Planning via Penalty Functions and Block-Coordinate Optimization

Eleftherios E. Vlahakis, Arash Bahari Kordabad, Lars Lindemann +3

Multi-agent planning under Signal Temporal Logic (STL) is often hindered by collaborative tasks that lead to computational challenges due to the inherent high dimensionality of the…

math.OC2025

GPU-Accelerated SPOCK for Scenario-Based Risk-Averse Optimal Control Problems

Ruairi Moran, Pantelis Sopasakis

This paper presents a GPU-accelerated implementation of the SPOCK algorithm, a proximal method designed for solving scenario-based risk-averse optimal control problems. The propose…

eess.SY2024

Conformal Prediction for Distribution-free Optimal Control of Linear Stochastic Systems

Eleftherios E. Vlahakis, Lars Lindemann, Pantelis Sopasakis +1

We address an optimal control problem for linear stochastic systems with unknown noise distributions and joint chance constraints using conformal prediction. Our approach involves…

eess.SY2024

Probabilistic Tube-based Control Synthesis of Stochastic Multi-Agent Systems under Signal Temporal Logic

Eleftherios E. Vlahakis, Lars Lindemann, Pantelis Sopasakis +1

We consider the control design of stochastic discrete-time linear multi-agent systems (MASs) under a global signal temporal logic (STL) specification to be satisfied at a predefine…

math.OC2024

NMPC for Collision Avoidance by Superellipsoid Separation

Ruairi Moran, Sheila Bagley, Seth Kasmann +5

This paper introduces a novel NMPC formulation for real-time obstacle avoidance on heavy equipment by modeling both vehicle and obstacles as convex superellipsoids. The combination…