Augmented manual fabrication methods for 2D tool positioning and 3D sculpting

Augmented manual fabrication involves using digital technology to assist a user engaged in a manual fabrication task. Methods in this space aim to combine the abilities of a human operator, such as motion planning and large-range mechanical manipulation, with technological capabilities that compensate for the operator's areas of weakness, such as precise 3D sensing, manipulation of complex shape data, and millimeter-scale actuation. This thesis presents two new augmented manual fabrication methods. The first is a method for helping a sculptor create an object that precisely matches the shape of a digital 3D model. In this approach, a projector-camera pair is used to scan a sculpture in progress, and the resulting scan data is compared to the target 3D model. The system then computes the changes necessary to bring the physical sculpture closer to the target 3D shape, and projects guidance directly onto the sculpture that indicates where and how the sculpture should be changed, such as by adding or removing material. We describe multiple types of guidance that can be used to direct the sculptor, as well as several related applications of this technique. The second method described in this thesis is a means of precisely positioning a handheld tool on a sheet of material using a hybrid digital-manual approach. An operator is responsible for manually moving a frame containing the tool to the approximate neighborhood of the desired position. The device then detects the frame's position and uses digitally-controlled actuators to move the tool within the frame to the exact target position. By doing this in a real time feedback loop, a tool can be smoothly moved along a digitally-specified 2D path, allowing many types of digital fabrication over an unlimited range using an inexpensive handheld tool.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2013

Author dc:creator

• Rivers, Alec (Alec Rothmyer)

Advisor dc:contributor.advisor

• Frédo Durand.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/79215

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/79215