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Systems & Control
The newest papers in Systems & Control that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
703 papers, from 31 August 2026 to 5 November 2026: 644 arXiv preprints and 59 OpenAlex records.
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Newest papers, page 15
Policy Synthesis for Finite Populations of MDP Agents under Aggregate Reach-Avoid Chance Constraints
Consider a finite population of agents with decoupled Markov transition dynamics and empirical-density feedback, subject to the following constraints: with probability at least $1-δ_r$, at least a…Leveraging Human-In-The-Loop Demonstrations in Reinforcement Learning for Digital Twin-Driven Robot Flexibility
Growing automation makes collaborative robots work in more variable environments, increasing the need for adaptation.A Physics-Informed Collision Learning Framework for Collaborative Robot Motion Generation
Close-proximity multi-arm manipulation requires collision models that are both geometrically accurate and differentiable enough for real-time optimization.FAITH: Feasibility-Aware Safety-Filtered RL for High-Dimensional Systems
Safe reinforcement learning commonly places safety and task performance in the same policy objective, where they can introduce competing updates.Image-Based Path-Planning for Navigation of Soft-Growing Robots in the Spinal Sub-Arachnoid Space
Recently, soft robotic procedures are being developed aiming at achieving targeted minimally invasive operations or drug administration in specific locations in the human body.Distributed Harmonic-Covariance Feedback for Hole Closure in Planar Robot Swarms
We consider hole closure in a planar multi-agent system whose sensing disks form a time-varying Čech complex.Robust and Scalable UAV-UGV Planning for Aerial Monitoring under Energy and Precedence Constraints
We consider planning for unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) teams in aerial monitoring missions with ordering requirements on the monitoring points to be visited by the…Verifier-Mediated Multi-LLM Coordination for Multi-Robot Path Planning
Foundation models are increasingly used for high-level multi-robot task planning, yet independently generated symbolic plans can become jointly infeasible after geometric grounding because of shared…Distributionally Robust Adaptive Iterative Covariance Steering for Small-Body Proximity Operations
Autonomous small-body proximity operations require continuous-thrust guidance under uncertain gravity, solar-radiation pressure (SRP), and stochastic disturbances.Deploying RDMA for Distributed Inference and Training At Scale
RDMA can reduce communication overhead in distributed machine learning systems, but realizing these benefits in production requires more than replacing TCP.Beyond Nominal Equilibria: Risk-Averse Multi-Population Mean-Field Games
Recent advances in mean-field games and its multi-population variants enable large-scale heterogeneous multi-agent systems to be modeled through representative agents and their associated mean-field…Adaptive Risk-Certified Event-Triggered Replanning for Dynamic Navigation
Safe navigation in dynamic environments requires robots to plan under obstacle predictions whose errors are uncertain, non-stationary, and can induce rare but safety-critical failures.LLM-Enabled UAV Dispatch: A System-Level Survey and Taxonomy
Unmanned aerial vehicle (UAV) dispatch is beginning to move beyond isolated path planning and optimization-driven resource allocation toward system-level coordination supported by semantic reasoning…Precise SE(3) End-Effector Tracking in Whole-Body Humanoid Control
Precise end-effector tracking during humanoid whole-body motion is challenging due to floating-base oscillations, gravity, dynamic coupling, and locomotion-induced disturbances.Video-to-Model: Automatic Modeling of Deformable Linear Objects
This paper presents a video-to-model framework for automatically modeling the motion of a deformable suture thread from an input video.Transition Path Sampling Using Koopman Operators and Exit-Time Optimal Control
Sampling transitions between metastable states is a central problem in dynamical systems theory and molecular dynamics in particular.LLA-MPPI: Rapidly Adaptive Whole-body Control of Legged Robots with GPU-Accelerated Parallel Simulations
Real-time whole-body controllers for legged robots typically plan through a fixed nominal model and degrade when the deployed dynamics change.Learning infinite context windows in recurrent architectures via spatial neural computing
Recurrent neural networks (RNNs) offer linear-time scaling with sequence length while requiring only constant memory, yet they struggle to capture long-range dependencies due to vanishing gradients…Strategic Investment Decision Making for Value Creation in Energy Transition: A Reinforcement Learning Approach
The global challenge of climate change has driven significant steps to reduce CO2 emissions, guided by international agreements like the Paris Agreement of 2015.RFChipAgent: Multi-Agentic AI Flow for Analog/RF Chip Design
Analog/RF circuits remain the critical interface between digital computation and the physical world, and emerging standards from Wi-Fi 7 to 6G place stringent demands on them, yet analog/RF design…