This paper presents the development and integration of a vision-guided loco-manipulation pipeline for Northeastern University's snake robot, COBRA. The system leverages a YOLOv8-based object detection model and depth data from an onboard stereo camera to estimate the 6-DOF pose of target objects in real time. We introduce a framework for autonomous detection and control, enabling closed-loop loco-manipulation for transporting objects to specified goal locations. Additionally, we demonstrate open-loop experiments in which COBRA successfully performs real-time object detection and loco-manipulation tasks.
@article{arxiv.2503.18308,
title = {Vision-Guided Loco-Manipulation with a Snake Robot},
author = {Adarsh Salagame and Sasank Potluri and Keshav Bharadwaj Vaidyanathan and Kruthika Gangaraju and Eric Sihite and Milad Ramezani and Alireza Ramezani},
journal= {arXiv preprint arXiv:2503.18308},
year = {2025}
}