Vision-Guided Loco-Manipulation with a Snake Robot

2025-03-24

AI Summary

To address the challenge of autonomous locomotion-manipulation for the COBRA snake robot in unstructured environments, this work introduces the first end-to-end vision-guided locomanipulation system. Methodologically, it integrates YOLOv8 for real-time object detection with binocular stereo vision, proposes a lightweight 6-DOF pose estimation algorithm, and designs a closed-loop feedback control strategy based on kinematic modeling. This enables, for the first time, full 6-DOF closed-loop locomotion-manipulation coordination on a snake robot. Experiments in realistic settings demonstrate robust performance across object detection, 6-DOF pose estimation, grasping, transport, and millimeter-precision placement—achieving >15 FPS while significantly enhancing task robustness and real-time responsiveness. This work establishes a scalable, perception-planning-control integrated paradigm for autonomous operation of soft and hyper-redundant robots.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Vision for Robotics & Autonomous Driving
• Natural Language Processing: Safety and Robustness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

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.

Problem

• Develop vision-guided loco-manipulation for snake robot COBRA
• Estimate 6-DOF object pose using YOLOv8 and stereo camera
• Enable autonomous object transport to goal locations

Innovation

• YOLOv8-based real-time object detection
• Stereo camera for 6-DOF pose estimation
• Closed-loop autonomous loco-manipulation control