activity
20172022
most citedNon-Parametric Neuro-Adaptive Control Subject to Task Specifications

3 citations · 4 across the 8 of their papers we have counts for

collaborators

11 papers

eess.SY20221 cited

Planning and Control of Multi-Robot-Object Systems under Temporal Logic Tasks and Uncertain Dynamics

Christos K. Verginis, Yiannis Kantaros, Dimos V. Dimarogonas

We develop an algorithm for the motion and task planning of a system comprised of multiple robots and unactuated objects under tasks expressed as Linear Temporal Logic (LTL) constr…

cs.AI2021

Deceptive Decision-Making Under Uncertainty

Yagiz Savas, Christos K. Verginis, Ufuk Topcu

We study the design of autonomous agents that are capable of deceiving outside observers about their intentions while carrying out tasks in stochastic, complex environments. By mod…

cs.RO20213 cited

Non-Parametric Neuro-Adaptive Control Subject to Task Specifications

Christos K. Verginis, Zhe Xu, Ufuk Topcu

We develop a learning-based algorithm for the control of autonomous systems governed by unknown, nonlinear dynamics to satisfy user-specified spatio-temporal tasks expressed as sig…

eess.SY2021

Safety-Constrained Learning and Control using Scarce Data and Reciprocal Barriers

Christos K. Verginis, Franck Djeumou, Ufuk Topcu

We develop a control algorithm that ensures the safety, in terms of confinement in a set, of a system with unknown, 2nd-order nonlinear dynamics. The algorithm establishes novel co…

cs.RO2021

KDF: Kinodynamic Motion Planning via Geometric Sampling-based Algorithms and Funnel Control

Christos K. Verginis, Dimos V. Dimarogonas, Lydia E. Kavraki

We integrate sampling-based planning techniques with funnel-based feedback control to develop KDF, a new framework for solving the kinodynamic motion-planning problem via funnel co…

math.OC2021

On Minimizing Total Discounted Cost in MDPs Subject to Reachability Constraints

Yagiz Savas, Christos K. Verginis, Michael Hibbard +1

We study the synthesis of a policy in a Markov decision process (MDP) following which an agent reaches a target state in the MDP while minimizing its total discounted cost. The pro…