There are considerable advantages in using products like Rhinoceros and Grasshopper, Robots for Grasshopper, and KUKA|PRC. Software and plugins enhance the control of industrial arm robots like the Universal Robotics UR10 or the KUKA range of robots, allowing users to create 3D simulations the robot moves or performs a complete task.
Rhinoceros (also called Rhino 3D, or Rhino) is a Computer-Aided Design (CAD) software used for the design and modelling of 3D products. It is widely used in the industrial / product design professions, and also used in a variety of industries because of a large range of plug-in applications that enhance the options of the basic Rhino software. A major advantage of using Rhino over similar software packages is a plug-in application called Grasshopper. Grasshopper allows users to use a visual programming language that makes coding accessible to people with limited programming knowledge. By using Grasshopper, users can make rapid changes or explore many variations of 3D models using algorithms or simple commands. Grasshopper’s interface simplifies the creation of complex models, and with the right plug-ins – allows for other abilities such as robot control that can potentially fabricate.
Rhinoceros 3D software: Quick modelling, and straightforward control of robots. In this example a simulation of a UR10 robot is tracing a loop drawn in Rhino by the user.

Rhinoceros 3D software: Quick modelling, and straightforward control of robots. In this example a simulation of a UR10 robot is tracing a loop drawn in Rhino by the user.
Why Grasshopper?

Rhino and the Grasshopper plug-in have many advantages over other methods of robotic control systems. Rhino is primarily a 3D modelling application, so creating or editing the 3D simulation environment is controlled within one type of software. Once a model is created, it is easy to make adjustments to the location for setting up a robot in a real-world environment, as well as objects for the robot to interact with or avoid. The advantages of using Grasshopper include rapid workflows from virtual prototypes to production. Changes to the control of the program or the intended design can be made quickly and new fabrications can be created.
The example workflow (illustrated below) of this is the ROBOBLOX project by QUT Design Robotics and UQ Architectural Robotics. The project created over 100 unique polystyrene foam blocks cut by a hot-wire cutter attached to a KUKA industrial robot, for installation as an art piece.

RoboBlox Workflow
  • Creation of the 3D models for each unique design of the blocks in Rhino.
  • Grasshopper was used to create the path the robot would follow to cut each of the blocks, and this pathway is simulated to predict any errors.
  • Grasshopper was used again to send the commands to the robot for the real blocks to be cut from a large slab of polystyrene.
  • The unique polystyrene blocks were finished and installed on site.

The entire process from choosing a design, to installation, was fabricated quicker and with greater accuracy compared with a similar project completed without a robot.
Workflow from modelling to simulation to fabrication to installed product

Workflow from modelling to simulation to fabrication to installed product
Visual Coding

On a typical Windows PC, the Grasshopper interface, or canvas is clearly laid out (shown above). Menus at the top of the Grasshopper window allow users to switch between different panels of icons. Each icon provides an option or toolset – with additional downloadable plugins extending these panels of tools. A script in Grasshopper uses components that look like box-like containers, each one offering varying inputs, an altering function, and outputs. The example image shows a script made with components from the Robots plugin. This layout shows how the visual script is easily read by following the guidewires that connect the container’s transfer data. Changes made to the data at the beginning of the script alters later outcomes and using this method it is quick to visualise many alternative designs before sending the final design to the robot for fabricating. The advantage of this is that rapid prototyping and robotic fabrication can be achieved or experimented with a variety of adaptations through the use of one type of software.

The Future of Manufacturing

With support from the Innovative Manufacturing Cooperative Research Centre (IMCRC), Design Robotics is collaborating to present a range of new fabrication and vision systems solutions. The goal is simple – to design for human intelligence and optimize the relationship between people and machines.
Pushing the limits of industrial robotics is a move to empower people. Navigating the increasing complexity of manufacturing inevitably supports human experience and enhances skills acquisition. At its heart, this approach celebrates the best of what robots and machines can achieve – problem-solving, and the best of what humans can do – social intelligence and contextual understanding.

_ News

Smartgeometry Workshop and Conference

Research Fellow Dr Muge Belek Fialho Teixeira was selected to participate in a workshop at the Smartgeometry workshop hosted by the University of Toronto earlier this year. In this post, Muge reflects on the workshop and conference.

Smartgeometry was founded in 2001 and is now a biannual event.  It starts with four days of themed workshops followed by a two day conference. Smart Geometry (SG) workshops and conferences have been influential to many disciplines including architecture, design, engineering and mathematics. Originating as a collaboration between industry, researchers and academics, SG has always been a platform where innovative ideas become a reality, informing the potential needs of the disciplines towards a better future.
The workshops are called clusters and are organised around open calls coordinated by ‘cluster champions.’ Cluster champions are collaborative teams from academia and practice who get together to prepare a proposal, or a response, to a specific theme. SG’s open call encourages researchers, academics and industry to discuss possible research questions around the proposed theme and a research avenue, via a project. By working on this project, researchers and practitioners from industry and universities have a chance to see how these technologies can be applied. Participants for each of the clusters applied for a position via open calls with cluster briefs defined by cluster champions. Participants were selected, from a competitive, international pool of applicants, based on their background, research expertise and current interests.

The conference, which took place after the workshops furthered discussions around the workshop themes informed by different perspectives from multidisciplinary invited keynote speakers. The conference was curated in a way that would feed back into the outcomes from the workshops. In that manner, it was a dynamic conference, where the keynote speakers build on the work produced by the clusters and open up new agendas for future speculations. The conference was followed by Q&A sessions that allowed the workshop participants to engage with the keynote speakers openly. These exchanges also provided opportunities for future collaborations.
The University of Toronto hosted Smatgeometry under the theme “Machine Minds”, which revolved around machine learning and AI (Artificial Intelligence). Current discussions on machine learning and AI, generally consist of depressing scenarios of humans coming to an end or humans losing their jobs. Websites like “Will robots take my job?” are opening up discussions about how we should give away our passions for our professions. As a trending topic for many disciplines, SG focused on how machine learning and AI can be utilised for design and what could be some other positive and constructive ways of approaching this topic. The clusters explored the applicable areas of Machine Learning and AI, whereas the keynote speakers of the conference tried to create an understanding of what is machine learning and AI and its impact on our society, as well as the methods they use them in their practice.
The clusters at SG were:
–          Smart materials (Fibrous timber joints, Materials as probes)
–          Smart geometries (AI strategies for space frame design, Mind ex-machine)
–          Smart fabrication methodologies (Soft Office)
–          Smart and innovative ways of perceiving the environment (Behavioural Enviro[NN]ments, Data Mining the City, Fresh Eyes, Inside the Black Box, Sound and Signal)
All of them used cutting-edge technologies and customized software to define geometries. These technologies included interactive tables, VR headsets, industrial robots, mobile robots, CNC routers, sensors, microphones, and many more. One of the most dominant software platforms used by clusters was Rhino with the Grasshopper plug in, as a unifying platform, but there was also other software such as Unity, Processing, Arduino, Python, or custom build software for the clusters. More information on each of the clusters can be found here.
Highlights from conference discussions were;
–          what is AI and machine learning,
–          how AI and machine learning will affect the future of societies and how we can get prepared,
–          collecting, interpreting and managing data,
–          natural intelligence versus digital intelligence,
–          machine learning versus human learning,
–          robotics and advanced manufacturing,
–          interactive installations,
–          complex geometries.
The schedule and the keynote speakers can be found here.
As part of the SG2018 there was also a trip to see the new workplace of Autodesk Toronto. Autodesk has been a close collaborator of SG as a sponsor and providing know-how, keynote speakers, cluster champions and event participants. The new Autodesk workplace has been designed using generative algorithms and has a research centre for exploring new technologies. One of the clusters (Mind ex Machina) took place in this research centre, using two UR10 collaborative robotic arms with custom build open source software for SG18. It seems Autodesk has started to take a pioneering role in research by collaborating with research institutions, researchers and companies through these research centres. With artist-in-residency programs, they are opening up their facilities globally to makers and curious minds. A list of Autodesk research centres can be found here.
Looking forward to the future, next Smartgeometry will take place at Carnegie Mellon University in Pittsburgh, USA, 2020 with another challenging theme!