A Quantum Annealing Approach to Target Tracking
Michel Barbeau, Farrokh Janabi-Sharifi, Houman Masnavi
Abstract
This paper delves into the fusion of quantum computing and robotics, focusing on motion planning in cluttered environments. Traditional algorithms struggle with complex problems where many constraints need to be satisfied. Hence, optimization-based approaches such as Constrained Quadratic Models (CQM) have become increasingly popular. Our work presents a 3D tracking algorithm based on CQM uniquely adapted for quantum computers to address computational challenges. With their parallel processing capabilities, Quantum computers offer a groundbreaking approach to optimizing complex problems. We formulate the CQM problem for efficient resolution on the D-Wave quantum computer, showcasing its superiority over classical counterparts. Our application centers on real-time planning in a target-chaser tracking scenario, highlighting the quantum advantage in handling the computation complexity of constrained problems. This paper bridges the quantum-robotics gap and sets the stage for future research in quantum-enhanced robotic motion planning.
BibTeX
@inproceedings{icra2025_aquantumannealin,
title = {A Quantum Annealing Approach to Target Tracking},
author = {Michel Barbeau and Farrokh Janabi-Sharifi and Houman Masnavi},
booktitle = {ICRA 2025},
year = {2025}
}