Industrial Dual-Arm Box Handling via Online Inertial Estimation and Convex Wrench Optimization
It addresses the practical problem of industrial dual-arm robots handling boxes with unknown inertial properties, offering a principled approach to stable manipulation.
This paper presents a friction-aware dual-arm box-handling framework that estimates unknown mass and center of mass online and computes friction-feasible contact forces via convex optimization, achieving stable lifting without slip or excessive squeezing in experiments.
Industrial robotic object handling often involves boxes and packages whose mass and center of mass are not known in advance. These uncertainties affect the force--moment balance required for stable lifting, and improper regulation of contact wrenches can lead to slip, object drop, orientation deviation, or excessive squeezing. This paper presents a friction-aware dual-arm box-handling framework for objects with unknown inertial properties. The proposed approach estimates the object mass and center of mass online from measured contact wrenches, and computes friction-feasible contact forces and torsional moments through a second-order cone program (SOCP) under ellipsoidal friction-limit-surface constraints. An offline trajectory refinement stage is also included to reduce undesired object--environment contact when geometric constraints are present. By enforcing friction feasibility as a hard constraint and minimizing contact effort within the feasible region, the framework achieves stable lifting without treating slip avoidance and excessive squeezing as separately tuned objectives. Experiments on a real dual-arm robotic system under different center-of-mass configurations demonstrate that the method lifts objects with unknown inertial properties while maintaining stable frictional contact.