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New QP Solver Handles Infeasible Robotics Problems

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced Elastic ODYN, a novel primal-dual non-interior-point quadratic programming (QP) solver designed to handle infeasible problems in robotics and control. Unlike existing methods that assume feasibility, Elastic ODYN uses smooth squared-$\ell_2$ elastic relaxations to manage conflicting objectives and modeling errors, ensuring stable gradients and convergence even when constraints cannot be met. This framework enables the development of an infeasibility-aware differentiable QP layer and an SQP method, which have been evaluated on various robotics tasks, demonstrating improved robustness and reliability over current state-of-the-art elastic QP solvers. AI

RANK_REASON Academic paper detailing a new method for solving quadratic programming problems in robotics. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New QP Solver Handles Infeasible Robotics Problems

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Academic paper detailing a new method for solving quadratic programming problems in robotics. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Aristotelis Papatheodorou, Jose Rojas, Ioannis Havoutis, Carlos Mastalli ·

    Elastic ODYN: Differentiable Optimization for Infeasible Control and Learning in Robotics

    arXiv:2606.16564v1 Announce Type: cross Abstract: Robotic systems routinely encounter conflicting objectives, modeling errors, and degenerate contact conditions that render quadratic programs (QPs) infeasible. Yet most optimization solvers and differentiable QP layers assume feas…

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