Deep Learning Based Robot for Automatically Picking up Garbage on the Grass

TL;DR

This paper introduces a deep learning-based robot capable of autonomously detecting and collecting garbage on grass surfaces, demonstrating high accuracy and efficiency in outdoor cleaning tasks.

Contribution

The paper presents a novel robot with integrated deep neural networks for ground segmentation, garbage recognition, and navigation, enhancing autonomous outdoor garbage collection.

Findings

Garbage recognition accuracy reaches 95%.

Navigation strategy achieves near traditional cleaning efficiency without path planning.

Robot effectively assists in outdoor garbage cleaning tasks.

Abstract

This paper presents a novel garbage pickup robot which operates on the grass. The robot is able to detect the garbage accurately and autonomously by using a deep neural network for garbage recognition. In addition, with the ground segmentation using a deep neural network, a novel navigation strategy is proposed to guide the robot to move around. With the garbage recognition and automatic navigation functions, the robot can clean garbage on the ground in places like parks or schools efficiently and autonomously. Experimental results show that the garbage recognition accuracy can reach as high as 95%, and even without path planning, the navigation strategy can reach almost the same cleaning efficiency with traditional methods. Thus, the proposed robot can serve as a good assistance to relieve dustman's physical labor on garbage cleaning tasks.