Automated Assistance for Small Tools and Materials

This project started as a research about how to improve time and material resources in construction sites.

Based on previous researchs, is possible to find construction workers can only contribute with 29% or their time productive labor. Rest of the working time is wasted in material waiting, tool waiting, material handling and movement.

How can we improve working time and help to increase production rates?

Requirements

-Raspberry pi 4 -Gripper with servo motor -Raspberry camera -OpenCV Phyton -Zbar code reader

Getting started

Analizing the actual behaviour in construction sites, we designed a protocol for tool demand and deliver.

First install OpenCV on Raspberry Pi and the libraries for face recognition and servo: haarcascade_frontal_face, Raspberry pi drivers for Raspberry camera,dlib, OS libraries.

Demo 1: Face Recognition-Labour X

Demo 2: Face Recognition and Gripper open/close

Automated Assistance is a project of IAAC, Institute for Advanced Architecture of Catalonia
developed at Master in Robotics and Advanced Construction in 2019/20 by:
Students: Muhammad Mansoor Awais, Maria Isabel Cousseau, Amit Pattar, Beril Serbes
Faculty: Angel Muñoz