Architecture for Industry 4.0-based

Manufacturing Systems

Achal Arvind

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CMU-RI-TR-16-43

July 2016

School of Computer Science

Carnegie Mellon University

Pittsburgh, PA 15213

Thesis Committee:

Stephen Smith

Zachary Rubinstein

David Bourne

Chung-Yao Chuang

Submitted in partial fulfillment of the requirements

for the degree of Master of Science in Robotics.

Copyright

c 2016 Achal Arvind

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AS01CH19_Mason ARI 19 February 2018 14:24

Annual Review of Control, Robotics, and

Autonomous Systems

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Toward Robotic Manipulation

Matthew T. Mason

Robotics Institute and Computer Science Department, Carnegie Mellon University, Pittsburgh,

Pennsylvania 15213, USA; email: matt.mason@cs.cmu.edu

Annu. Rev. Control Robot. Auton. Syst. 2018.

1:19.1–19.28

The Annual Review of Control, Robotics, and

Autonomous Systems is online at

control.annualreviews.org

https://doi.org/10.1146/annurev-control-060117-

104848

Copyright c 2018 by Annual Reviews.

All rights reserved

Keywords

robot, manipulation, evolution, engineering

Abstract

This article surveys manipulation, including both biological and robotic manipulation.

Biology inspires robotics and demonstrates aspects of manipulation

that are far in the future of robotics. Robotics develops concepts and

principles that become evident only in the creative process. Robotics also

provides a test of our understanding. As Richard Feynman put it: “What I

cannot create, I do not understand.”

19.1

Review in Advance first posted on

March 1, 2018. (Changes may still

occur before final publication.)

Annu. Rev. Control Robot. Auton. Syst. 2018.1. Downloaded from www.annualreviews.org

Access provided by 106.186.119.115 on 05/25/18. For personal use only.

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The motion of the camera can cause images of pedestrians to be captured at extreme angles. This can lead to very poor pedestrian detection performance when using standard pedestrian detectors. To address this issue, we propose a Rotational Rectification Network (R2N) that can be inserted into any CNN-based pedestrian (or object) detector to adapt it to significant changes in camera rotation.

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本文档是卡耐基梅隆大学机器人研究所的技术论文。

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This paper describes computer vision techniques for early-season measurement of vine canopy parameters; leaf count, leaf area and shoot count.

本文档是卡耐基梅隆大学机器人研究所的技术论文。

Keywords: Reinforcement Learning, Robotic Manipulation, Automatic Curriculum

Generation

本文档是卡耐基梅隆大学机器人研究所的技术论文。

Deploying a system that probes the subsurface brings its own challenges and to that end, we designed, built and field tested an autonomous robot that can collect subsurface samples using a 1m drill.

This paper describes the robot and science instruments and lessons from designing and operating such a system.

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本文档是卡耐基梅隆大学机器人研究所的技术论文。

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Our method yields R-squared correlation of 0.88 for stalk count and a mean absolute error of

2.77mm where average stalk width is 14.354mm. Our approach is 30 times faster for stalk count and 270 times faster for stalk width measurement.

本文档是卡耐基梅隆大学机器人研究所的技术论文。

Looking Forward: A Semantic Mapping System for Scouting with Micro-Aerial Vehicles

Our ultimate goal is to enable MAVs to perform autonomous scouting. In this paper, we describe a semantic mapping system designed to support this goal. The system maintains a 2.5D map describing its belief about the location of semantic classes of interest, using forward-looking cameras and state estimation.

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本文档是卡耐基梅隆大学机器人研究所的技术论文。

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