Ergodic Control

Latest papers

9 papers2 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Time-Optimal Ergodic Retrieval
Oct 15, 2026Christian Sulana, Christian Hughes, Ian AbrahamErgodic Control Robotic Object Search
Christian Sulana is with Saddleback College, Mission Viejo, California, USA · Christian Hughes is with the Department of Mechanical Engineering, Yale University, New Haven, CT 06520, USA · Ian Abraham is with the School of Electrical and Computer Engineering, The University of Sydney, Sydney, Australia
Safe Ergodic Control for Multi-Robot Systems via Quadratic Programming
Oct 4, 2026Yo Toyomoto, Mohamed Elobaid, Bryce L. Ferguson +2Multi-Robot Systems Control Barrier Functions
Electrical and Computer Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia · Thayer School of Engineering at Dartmouth College, Hanover, NH, USA · Department of Computer Science, Dartmouth College, Hanover, NH, USA
Ergodic Control and Controlled Diffusion for Robot Learning: Review and Tutorial
Sep 9, 2026Max Muchen Sun, Cem Bilaloglu, Ananya Rao +6Ergodic Control Robot Learning
Northwestern University · Idiap Research Institute · Carnegie Mellon University +4
SAGE: Ergodic Control for Autonomous and Adaptive Inspection of Subsea Infrastructure
Aug 20, 2026Markus Buchholz, Ignacio Carlucho, Yvan R. PetillotErgodic Control Robotic Inspection
Norwegian Defence Research Establishment (FFI), Kjeller, Norway. · School of Engineering & Physical Sciences, Heriot-Watt University, Edinburgh, UK.
ErgoSurf: Ergodic Control for the Coverage of Unknown Surfaces
Aug 6, 2026Stefan Schneyer, Timo Bachmann, Maged Iskandar +4Mobile Robotics Ergodic Control
German Aerospace Center (DLR), Institute of Robotics and Mechatronics (RM), Münchener Str. 20, 82234 Weßling, Germany · Technical University of Munich (TUM); School of Computation, Information and Technology; Boltzmannstr. 3, 85748 Garching, Germany
TRACE: Ergodic Trajectory Optimization for Active Scene Reconstruction
Aug 3, 2026Ziyue Zheng, Linli Shi, Bingkun He +2Trajectory Optimization Trajectory Generation
1Johns Hopkins University, USA · University of Pennsylvania, USA
Ergodic Imitation for Adaptive Exploration around Demonstrations
May 13, 2026Ziyi Xu, Cem Bilaloglu, Yiming Li +1Imitation Learning Learning from Demonstration
Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland · Idiap Research Institute, Martigny, Switzerland
Infinite-Horizon Ergodic Control via Kernel Mean Embeddings
Apr 1, 2026Christian Hughes, Ian AbrahamErgodic Control Optimal Control
Manufacturing Micro-Patterned Surfaces with Multi-Robot Systems
Mar 18, 2026Annalisa T. Taylor, Malachi Landis, Ping Guo +1Ergodic Control Robotics
Mechanical Engineering Department, Northwestern University

Oct 15, 2026J/K move · Enter open · S save

Time-Optimal Ergodic Retrieval

Christian Sulana, Christian Hughes, Ian Abraham

Christian Sulana is with Saddleback College, Mission Viejo, California, USA · Christian Hughes is with the Department of Mechanical Engineering, Yale University, New Haven, CT 06520, USA · Ian Abraham is with the School of Electrical and Computer Engineering, The University of Sydney, Sydney, Australia

Ergodic Control Robotic Object Search Robot Motion Planning Robotic Optimization Autonomous Robot Exploration Stochastic Optimal Control

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Retrieval tasks are a form of search task where a robot must explore, find an object, and return with it as quickly as possible. Recent work in ergodic control has demonstrated time-optimal path planning for search tasks where visitation is proportionally matched, within some tolerance, to a given target distribution. However, these planners minimize the duration of a full deterministic search, while retrieval missions end their search at an unknown point in the trajectory and must return to a given base. In this work, we propose a new formulation of the time-optimal ergodic search problem that models detection as a Poisson process and minimizes total mission time by including the return phase in the objective. Experimental results show that time-optimal ergodic retrieval (TOER) achieves up to

19\%

shorter mission durations relative to ergodic baselines and that this advantage grows as the return phase becomes more costly. Simulation and hardware implementations validate TOER's compatibility with environments of non-convex geometry as well as both 2D and 3D search domains.