Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/77710
Title: Adaptive and flexible robotic pick-and-place
Authors: Cahaya, Ryan Eka
Keywords: DRNTU::Engineering::Mechanical engineering
Issue Date: 2019
Abstract: FMCG industry is trending towards e-commerce adoption. However, there are challenges in the existing packaging lines. One of the main challenges is to pack products in accordance to mass customized orders. In this project, we aim to develop an automated solution for this challenge in bin picking scenario, which is picking up object from a clustered bin. The robot system setup consists of a robotic arm equipped with gripper, a 2D/3D camera. The robot system is able to detect FMCG products (object detection) and to calculate the pose of the product (pose estimation). This paper aims to show several aspects of developing the solution: ROS architecture development, perception, and motion planning. There are two perception methods proposed in this paper: feature matching (SIFT) and deep learning (Mask R-CNN). Each method will be described in detail.
URI: http://hdl.handle.net/10356/77710
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:MAE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
Ryan FYP report final.pdf
  Restricted Access
FYP Report3.92 MBAdobe PDFView/Open

Page view(s)

75
Updated on Mar 5, 2021

Download(s) 50

38
Updated on Mar 5, 2021

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.