Pose graph optimization is recast as damped Riemannian dynamics on Lie groups, enabling a fully distributed algorithm with a semi-implicit integrator that converges under both synchronous and asynchronous communication.
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12 Pith papers cite this work. Polarity classification is still indexing.
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The paper introduces diagnostic certificates that separately assess state-space coverage, lifted-feature nondegeneracy, and regression-spectrum quality for Koopman and EDMDc identification, with theoretical guarantees on the smallest singular value under a population spectral gap.
Timed reward machines extend reward machines with timing constraints, allowing model-free RL algorithms to learn policies that satisfy precise temporal requirements on standard benchmarks.
SODA uses differential algebra and adaptive Gaussian mixtures to solve chance-constrained nonlinear trajectory optimization problems for space missions with non-Gaussian uncertainties.
A mixed formulation for Cosserat rod dynamics is cast as an infinite-dimensional nonlinear port-Hamiltonian system and discretized with structure-preserving finite elements to yield energy-momentum consistent time integration.
Two general-purpose methods transcribe multi-dimensional Gaussian chance constraints for trajectory optimization with reduced conservatism, paired with a quadratic-complexity risk estimator that remains accurate in high dimensions.
Reddit analysis finds MAHA users show strong cross-theme belief bundling and network coherence unlike anti-MAHA users, with pandemic-era shifts from anti-fluoride/mask to anti-vaccine to broader anti-science engagement.
A port-Hamiltonian modeling, ISS control, and energy-conserving simulation framework for grid-forming SVGs that outperforms PI control and standard integrators in numerical tests.
Koopman operators identified from Bekker-Wong terramechanics simulations enable short-horizon prediction and constrained MPC for stable tracking of aggressive maneuvers by off-road vehicles on deformable terrain.
A filter line search SQP algorithm reduces iterations and computation time for nonconvex SOS programs compared to prior methods.
Overlapping Schwarz decomposition for nonlinear OCPs achieves local linear convergence with rate improving exponentially with overlap size, based on exponential decay of sensitivity for primal and dual solutions.
Replicates SPARK humanoid safety filters and stress-tests them under crowding, noise, and delays, showing trade-offs in goal tracking versus collision reduction.
citing papers explorer
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Distributed Pose Graph Optimization via Continuous Riemannian Dynamics
Pose graph optimization is recast as damped Riemannian dynamics on Lie groups, enabling a fully distributed algorithm with a semi-implicit integrator that converges under both synchronous and asynchronous communication.
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Diagnostic Certificates of Data Quality and Regression Identifiability for Koopman Identification
The paper introduces diagnostic certificates that separately assess state-space coverage, lifted-feature nondegeneracy, and regression-spectrum quality for Koopman and EDMDc identification, with theoretical guarantees on the smallest singular value under a population spectral gap.
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About Time: Model-free Reinforcement Learning with Timed Reward Machines
Timed reward machines extend reward machines with timing constraints, allowing model-free RL algorithms to learn policies that satisfy precise temporal requirements on standard benchmarks.
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Non-linear stochastic trajectory optimisation
SODA uses differential algebra and adaptive Gaussian mixtures to solve chance-constrained nonlinear trajectory optimization problems for space missions with non-Gaussian uncertainties.
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Mixed formulation and structure-preserving discretization of Cosserat rod dynamics in a port-Hamiltonian framework
A mixed formulation for Cosserat rod dynamics is cast as an infinite-dimensional nonlinear port-Hamiltonian system and discretized with structure-preserving finite elements to yield energy-momentum consistent time integration.
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Chance constraints transcription and failure risk estimation for stochastic trajectory optimisation
Two general-purpose methods transcribe multi-dimensional Gaussian chance constraints for trajectory optimization with reduced conservatism, paired with a quadratic-complexity risk estimator that remains accurate in high dimensions.
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The Structure and Dynamics of the Online MAHA-sphere
Reddit analysis finds MAHA users show strong cross-theme belief bundling and network coherence unlike anti-MAHA users, with pandemic-era shifts from anti-fluoride/mask to anti-vaccine to broader anti-science engagement.
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Port-Hamiltonian Control and Structure-Preserving Algorithm for Grid-Forming SVGs
A port-Hamiltonian modeling, ISS control, and energy-conserving simulation framework for grid-forming SVGs that outperforms PI control and standard integrators in numerical tests.
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Koopman Operator Framework for Modeling and Control of Off-Road Vehicle on Deformable Terrain
Koopman operators identified from Bekker-Wong terramechanics simulations enable short-horizon prediction and constrained MPC for stable tracking of aggressive maneuvers by off-road vehicles on deformable terrain.
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On the Practical Implementation of a Sequential Quadratic Programming Algorithm for Nonconvex Sum-of-squares Problems
A filter line search SQP algorithm reduces iterations and computation time for nonconvex SOS programs compared to prior methods.
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On the Convergence of Overlapping Schwarz Decomposition for Nonlinear Optimal Control
Overlapping Schwarz decomposition for nonlinear OCPs achieves local linear convergence with rate improving exponentially with overlap size, based on exponential decay of sensitivity for primal and dual solutions.
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Adversarial Stress Testing of SPARK Humanoid Safety Filters
Replicates SPARK humanoid safety filters and stress-tests them under crowding, noise, and delays, showing trade-offs in goal tracking versus collision reduction.