A geometric method for base-parameter analysis in robot inertia identification based on projective geometric algebra

Abstract

This paper proposes a novel geometric method for analytically determining the base inertial parameters of robotic systems. The rigid body dynamics is reformulated using projective geometric algebra, leading to a new identification model named “tetrahedral-point (TP)” model. Based on the rigid body TP model, coefficients in the regressor matrix of the identification model are derived in closed-form, exhibiting clear geometric interpretations. Building directly from the dynamic model, three foundational principles for base-parameter analysis are proposed: the shared points principle, fixed points principle, and planar-rotations principle. With these principles, algorithms are developed to automatically determine all the base parameters. The core algorithm, referred to as Dynamics Regressor Nullspace Generator (DRNG), is non-symbolic yet fully analytical. It provides an efficient solution that is universally applicable to a wide range of robotic architectures, including both fixed-base and floating-base systems, as well as open-chain and closed-chain configurations. The proposed method and algorithms are validated across four robots: Puma560, Unitree Go2, a 2RRU-1RRS parallel kinematics mechanism (PKM), and a 2PRS-1PSR PKM. In all cases, the algorithms successfully identify the complete set of base parameters. Notably, the approach demonstrates high robustness and computational efficiency, particularly in the cases of PKMs. Through the comprehensive demonstrations, the method is shown to be general, robust, and efficient.