Sustainability Vectors // Machine Vision Project Ideation

Today

• Introduction to Sustainability in Robotics
• Project Ideation, Team Formation, and Proposals

For Next Time

• Work on the Broader Impacts assignment Part 2, due on November 5th at 7PM
  • Note – discussions will happen on October 28th, October 31st, and November 4th; you have been randomly assigned one of these days to lead a discussion. You may swap slots with someone on a different day, but you have to let an instructor know. Thanks!
• Read over the Machine Vision Project Document.
  • Project Proposal is due on Tuesday October 22nd at 7PM. We’ll have some in-class time today to work on this.
• Consider whether there is feedback you’d like to share about the class

Sustainability in Robotics

As we kickoff a new module, we’ll be examining a new contextual theme: sustianability. Sustainability is commonly applied to three key “vectors” –

• People / Social – creating well-being of people and communities
  • Some topics include, e.g., socioeconomic equality and equity, access to resources, fair governance, education, human rights, etc.
• Planet / Environmental – preserving and protecting the natural environment
  • Some topics include, e.g., biodiveristy, air/water/soil quality, climate regulation, natural resource management, etc.
• Products / Economic – enabling and preserving long-term economic well-being
  • Some topics include, e.g., resource management, efficiency, innovation, policy and social equity, financial stability, etc.

Discussion Question (8 minutes): How do you think robots fit into each of these vectors (either as a tool, or as an industry itself)? Do you have some examples of robots or companies that you could map to these vectors?

Throughout this module, we’ll be taking a look at how machine vision is adapted into a very particular type of robotic system: waste collectors / recyclers –

• Automated Sorting in Recycling Plants (e.g., rStream and a deep dive into this paper)
• Automated Waste Collection (e.g., Ocean CleanUp and a deep dive into papers on bespoke solutions)

Discussion Question (8 minutes): In what ways do you think machine vision may be used in waste sorting / cleaning? What design characteristics would these algorithms need in order to be used in these applications?

Machine Vision Ideation and Team Formation

Take a look at the machine vision project assignment document – today we’ll be forming teams, brainstorming project ideas, and starting your project proposals.

Process:

• [5 min] Individually review your learning goals for the class and for this project
• [5 min] Create a sticky-note for each topic/theme you’d like to explore in this project. Consider:
  • Is there a particular application of machine vision you’d like to investigate?
  • Is there a particular class of algorithm you’d like to learn about?
  • Is there a particular algorithm you’d like to implement or dataset you’d like to use?
• [5 min] Gather with 2 other folks and rapid-sort your sticky-notes into clusters on a white board – label your clusters
• [5 min] As a class, we’ll identify 6 common themes and place them around the room
• [10 min] Choose a theme that interests you and go to it in the room; with the other folks in the group, discuss your learning goals and ideas you have related to that theme
  • You’re not committing to anything yet! This is about exploring some areas and project ideas of interest
• [10 min] Pick another theme and go to it; repeat your discussions
  • You’re not committing to anything yet! This is about exploring some areas and project ideas of interest
• [Rest of Class Time] Find a partner and begin to scope a project you’d like to complete. You can use the proposal guidelines to frame your discussion