SOURCE-LINKED INTELLIGENCE

ElastiQP: An Always-Feasible QP Solver for Constrained Robot Control

arXiv · AI, language, vision and robotics · article · Sep 16, 2026 · UTC

As robot capabilities increase, quadratic programming (QP)-based controllers must account for a similarly increasing number of constraints to ensure safe, reliable operation. Yet, with each added constraint, this introduces more chances of momentary conflict: in which case, a QP solver that returns an "infeasible" status leaves the controller with nothing to execute. To address this, we introduce ElastiQP, a modified dual active-set QP solver that relaxes every inequality constraint with an exact, per-constraint l1 penalty while keeping equality constraints (dynamics) hard. Notably, ElastiQP d

Read original source ↗ Open in workspace

recordType

paper

region

Global