Grants

AABM: Aerial Additive Building Manufacturing

March 2016 - January 2020

Additive Building Manufacturing (ABM) is transforming the construction industry through the 3D printing of buildings and building components. A number of countries are now demonstrating ABM can substantially reduce construction time, material and transport costs, improve worker safety standards and alleviate construction's impact on urban traffic congestion and the environment. ABM also provides geometrical variety at no additional cost. In contrast to most manufacturing sectors, variety is a necessity within construction to satisfy different client requirements and adapt to unique terrain, boundary and laws governing each physical site.

However, current ABM systems are difficult to deploy on construction sites due to their large size and fixed 3D Print build volumes that are not sufficiently flexible to deal with the complexities of most building scenarios, or provide adequate measures for human safety. These ABM technologies are unable to undertake maintenance and repair work, or construct buildings in many urban or elevated sites. They are also not able to be utilised for post-disaster reconstruction activities where their manufacturing speed would be of great assistance.

To address this limitation, this research proposal aims to develop the world's first Aerial Additive Building Manufacturing (Aerial ABM) System consisting of a swarm of aerial robots (Unmanned Aerial Systems (UAS)) that can autonomously assess and manufacture building structures. Aerial ABM offers major improvements to human safety, speed, flexibility, and manufacturing efficiency compared to existing ABM and standard building construction technologies. We have already developed and demonstrated pilot results using UAS that can extrude 3D Print material during flight and we have developed simulation environments that allow for autonomous planning and execution of manufacturing with swarms of UAS working in collaboratively.
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Safe multicopter navigation in cluttered and dynamic environments

October 2018 - September 2022

The overarching goal of this project, funded by SLAMcore Ltd, is to develop unified multicopter control, motion-planning and collision avoidance technology that uses as a basis 3D occupancy maps including dynamic objects/people to be built in real-time on-board the robot.

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Swift, Reactive Aerial and Ground Inspection of Industrial Facilities (SWIFT)

November 2019 - January 2021

There is strong demand for autonomous inspection of industrial structures by aerial and ground robotic systems. A key goal for such robots is that the basic functions of mapping, localisation, exploration and path planning be carried out autonomously using onboard sensor payloads (LIDARs and camera). Such a mission involves autonomously taking off, carrying out a mapping or re-mapping mission and then returning to a base station. Additionally, for this technology to be advantageous to companies in the offshore industry, multiple robots will need to be deployed simultaneously by a single operator, which requires high levels of robot autonomy.
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Smart control room for constructionindustry, powered by 3D AI

April 2020 - May 2021

Together with the Civil Engineering Department (Co-I Prof. Jennifer Whyte) and Contilio, a fast-growing construction tech startup, we aim to develop technologies for automated construction progress monitoring. The approach will leverage 3D reconstruction, Deep Learning, Scan-vs-BIM and Scan-to-BIM techniques, drawing on the expertise in Robotics, Computer Vision, BIM, and construction progress monitoring available in both Imperial Departments and Contilio.
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