soibelman disruptive technologies disruptive... · 2018. 11. 22. · bim bi m astani department of...

2018/05/20

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Astani Department of Civil &Environmental Engineering

Disruptive Technologies in the Americas

Lucio Soibelman PhDViterbi Dean’s Professor and Department Chair

Astani Department of Civil and Environmental Engineering University of Southern California


USC

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University main Contribution to Disruptive technologies

• NAE GRAND CHALLENGES SCHOLARS PROGRAM– Research/creativity

• Mentored research or project experience related to a Grand Challenge:• TECHNICAL COMPETENCE

– Multidisciplinarity• Understanding gained through multidisciplinarity• SOFT SKILLS AND COMMUNICATIONS

– Entrepreneurship• Understanding gained through experience that viable business models are necessary• INNOVATION AND ENTREPRENEURSHIP

– Cultural Competence• Understanding gained through global or different cultural experience• GLOBAL and LOCAL

– Social consciousness• Addressing societal problems, through service learning, K-12, social entrepreneurship• SERVICE LEARNING; OUTREACH


BIM Usage (Smart Market Report from McGraw Hill)

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Pre-Fabrication – From ADEPT

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Labeled Components


Pre-Fabrication – From ADEPT

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Labeled Components

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Construction Process From Turner


Construction Process

From Turner

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BIM

BIM


Present/Future - Laser Scanning and Imaging Technologies for Generating 3D as-built Models

• A laser scan beamed in 360 degrees to generate a cloud of points of the scanned area in 3D

• Today we have sensors with mm accuracy, millions of points per scan, and acquisition rates well below one minute per scan

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3D Model Created From Point Cloud From Turner


Project history visualization environment

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Thank you!


Immersive Display – Cave – From Messner

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More Cave

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More Cave

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Virtual Reality Representation

• Goal is to integrate VR treadmill with HMD

so that the cyberlearning environment

offers a virtual construction site of its size

and dynamic nature similar to real

construction sites

– Include pre-programmed avatars that work side by side or collaboratively with the worker

– Several different work scenarios and environment conditions with robots

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Why Construction Robots?

• Construction industry is challenged by – Low productivity rates

– Safety concerns

– Shortage of skilled workers

• Construction sites can have tough work conditions such as– Dust and humidity

– Severe weather conditions (hot/cold)

– Lack of natural light (e.g. tunnels)

– Requires climbing (e.g. bridges)

– Toxic substances (e.g. lead)

• Construction tasks can be repetitive


Current Trend

• Construction industry has the opportunity to improve productivity and safety with advancements in construction automation

• This trend does not mean that construction robots will completely replace construction workers– Most construction robots are not fully autonomous

– Construction robots, slowly integrated into the construction industry, will replace certain construction tasks, but not jobs entirely [2]

– Construction workers will work side-by-side or collaboratively with construction robots

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Robotics in Construction

In the Market

Demolition RobotsBricklaying RobotsExoskeletonsWelding Robots

Started Emerging

Swarm Robotics3D Printing / Contour CraftingRepainting/Repaving RoadHumanoids


Bricklaying Robot

• SAM (Semi-Automated Mason)

• Faster production of walls Can lay around 2,000

bricks a day • Waste reduced• Designed to work alongside human workers

Source: Construction Robotics

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Bricklaying Robot SAM



Bricklaying Robot SAM


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Bricklaying Robot

• Hadrian

• Faster production of walls Can construct average

sized dwelling in two days• Waste reduced• Can be driven to the work site and be set up

• Does not require manual handling Source: Fastbrick Robotics,

https://www.iseekplant.com.au/blog/bricklaying‐robot‐1000‐bricks/


Bricklaying Robot Hadrian

Source: Fastbrick Robotics

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Demolition Robot

• Brokk Demolition Robot• Used for tearing down building

walls and structures

• Multi tooled Multiple types of tools placed at

the end of robotic arm

• Much more effective than handheld devices, safer for workers

• But, Requires large power source for bigger scaled projects

Source: Brokk Inc.


Demolition Robot

• Many other suppliers – Top Tec

– Husqvarna

Source: Husqvarna, Top Tec

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Demolition Robot

Source: https://www.youtube.com/watch?v=_8xjE1__JE8


Demolition Robot

Source: https://www.youtube.com/watch?v=_8xjE1__JE8

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Welding Robot

• MX3D Welding Robot

• Used for connecting and welding steel beams

• For constructing tall buildings, using welding robots can increase safety of workers

• Going for automated solutions

Less human involved

Source: MX3D,https://archpaper.com/2015/07/new‐robot‐technology‐dutch‐

designer‐can‐3d‐print‐steel‐bridge‐mid‐air‐canal/


Welding Robot

Source: MX3D

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Timber Construction

Source: Gudel


Swarm Robotics

Source: Harvard Wyss Institute

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Bridge Inspection

Source: Center for Autonomous Systems


Water & Wastewater Infrastructure

Source: RedZone

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Pictures from RedZone

Video Inspection

Digital Image Analysis & Computer Vision

Sewer Robotic Condition Assessment


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Hierarchical Infrastructure Assessment

• The Pareto Principle (80/20 rule)

Focus on the problem assets or assets of interest

315834 ft

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Computer-assisted Image Interpretation Approach

• Step 1: generation of SIFT local feature descriptors SIFT Approach for Defect Detection in Wastewater Pipes


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Tunnel Inspection

Source: Markforged


Exoskeletons

Source: CNN

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Humanoids

Source: UPHIGH productions, Toyota,https://www.youtube.com/watch?v=ItEhgLYlXZM&t=71s


Issues with Robotics in Construction

• Construction robots are not fully automated and therefore, will require collaboration with human workers

• Human workers might not trust the robots

• Establishing a natural collaboration can be hard

• New safety issues can emerge – Programming issues

– Unexpected work situations

• New social issues can emerge– Privacy of workers

– Fear of job loss

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$0.11/kWh

$0.25/kWh102 quads Primary Energy

40% Electricity 60% Other

73% Commercial and Residential Buildings

23% Other

EnablingEnergy‐AwareSmartFacilitiesCollaborationwithPhDStudentMarioBerges,andProfessorScottMatthews

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Motivation


DataAcquisition

A Bv t i t

v t i t

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FeatureExtraction

Delta,orchange:

<a>

Allsamples:

<a,b,c,d,…>

Linearregression:fitaline.

<a,b>

KernelRegression:

<a,b,…>


Vision

Low‐Cost High‐Value

soibelman disruptive technologies disruptive... · 2018. 11. 22. · bim bi m astani department of...

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