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.
View on arXiv@article{salagame2025_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 }
}