Digital twinDigital twin speeds up reinforcement learning for lab robotsarXiv API — полнотекстовый поиск "digital twin" · 23hDigital twinDataset for deciding between evidence gathering and action in control-system incidentsarXiv — Computational Engineering, Finance, and Science (cs.CE) · yesterdayDigital twinSparse stochastic twins can outperform exact digital twinsarXiv — Computational Engineering, Finance, and Science (cs.CE) · yesterdayModellingPluralism of rival models in network models of sciencearXiv — Multiagent Systems (cs.MA) · yesterdayForecastingEstimation and MPC for balancing a wheel-legged robot under unknown disturbancesarXiv — Systems and Control (eess.SY) · yesterdayDigital twinConsolidating dispersed DSO data into a digital twin of the distribution gridarXiv API — полнотекстовый поиск "digital twin" · 2dDigital twinIntegrating ML and uncertainty quantification for real-time decisions in digital twinsarXiv API — полнотекстовый поиск "digital twin" · 2dDigital twinBiases in end-to-end digital twins built from chained modelsarXiv API — полнотекстовый поиск "digital twin" · yesterdayDigital twinDistributed Bandits for Freshness-Aware Data in MEC-Enabled Digital TwinsarXiv API — полнотекстовый поиск "digital twin" · yesterdayModellingAn agent-based model of knowledge transfer across scientific communitiesarXiv — Multiagent Systems (cs.MA) · 2dDigital twinSemantic interoperability in federated digital twins: a systematic reviewarXiv — Systems and Control (eess.SY) · 2dDigital twinCalibrating persona-based digital twin simulation against real dataarXiv — Computers and Society (cs.CY) · 2d

Estimation and MPC for balancing a wheel-legged robot under unknown disturbances

US & West · yesterday

The paper combines moving horizon estimation with an offset-free, constrained MPC for sagittal balancing of a 9.95 kg wheel-legged robot. The estimator uses a virtual-leg model augmented with a hip force, a body pitch torque and a gyroscope bias, and process noise is raised when an impact is detected.

Why it matters

It demonstrates state estimation and constrained control under unknown disturbances, a core mechanism that transfers to larger managed systems.

Original headline: Moving Horizon Estimation and Constrained Model Predictive Control for Balancing a Wheel-Legged Robot Under Unknown Disturbances

Read the original: arXiv — Systems and Control (eess.SY)

Translation and summary are machine-generated from the source. The full article is not republished; its rights belong to the source.