Autonomous Grasping On Quadruped Robot With Task Level Interaction

TL;DR

This paper presents an autonomous grasping system for quadruped robots that integrates hardware, layered control, and web-based interaction, enabling effective object manipulation in real-world scenarios.

Contribution

It introduces a novel task-level interaction approach with hardware integration, layered control, and web interface for autonomous grasping on quadruped robots.

Findings

Achieved a 75% grasp success rate in real-world tests.

Enabled navigation, object detection, and grasping autonomously.

Demonstrated effective human-robot interaction via web interface.

Abstract

Quadruped robots are increasingly used in various applications due to their high mobility and ability to operate in diverse terrains. However, most available quadruped robots are primarily focused on mobility without object manipulation capabilities. Equipping a quadruped robot with a robotic arm and gripper introduces a challenge in manual control, especially in remote scenarios that require complex commands. This research aims to develop an autonomous grasping system on a quadruped robot using a task-level interaction approach. The system includes hardware integration of a robotic arm and gripper onto the quadruped robot's body, a layered control system designed using ROS, and a web-based interface for human-robot interaction. The robot is capable of autonomously performing tasks such as navigation, object detection, and grasping using GraspNet. Testing was conducted through real-world scenarios to evaluate navigation, object selection and grasping, and user experience. The results show that the robot can perform tasks accurately and consistently, achieving a grasping success rate of 75 % from 12 trials. Therefore, the system demonstrates significant potential in enhancing the capabilities of quadruped robots as service robots in real-world environments.