Task Correlation and Edge-Cost Estimation for Robotic Task Sequencing Problem in Torus C-Space

Abstract

Robotic manipulators are increasingly used in diverse applications, ranging from industrial automation to human-centered tasks such as grocery picking and packaging, where they are often required to perform sequences of tasks while maintaining motion optimality and collision-free operation over long horizons. This type of problem is known as the Robotic Task Sequencing Problem. Most existing works address this problem by reducing it to the Traveling Salesman Problem (TSP) and within a purely Euclidean framework, neglecting the robot’s inherently non-Euclidean toroidal mathcal{C}-space topology. This simplification limits the selection of feasible configurations and may lead to failure, suboptimal, or detoured motions. In this paper, we propose a robotic task sequencing problem solver that incorporates the robot’s natural mathcal{T}^n topology and joint limits.