Social Assistive Robotics

(Socially Intelligent Assistive Robotics)

Instructor: Dr. Elaine Schaertl Short

TA: Felix Gervits

Monday & Wednesday, 3-4:15pm

Office Hours: Wednesdays 4:30-5:30pm or by appointment

Welcome!

I’m excited that you’ve chosen to enroll in CS 150 Social Assistive Robotics! I am looking forward to sharing my knowledge about robotics with you and guiding you through doing research at the intersection of human-robot interaction and assistive robotics.

What does this course offer to you?

I have three main goals for you for this course:

• To familiarize you to a wide variety of research at the intersection of human-robot interaction and assistive robotics.
• To introduce you to software tools, computational techniques, and ethical considerations that enable this work.
• To give you a strong foundation in research methods that will allow you to be a successful robotics researcher in the future.

How, exactly, are you going to accomplish this?

The centerpiece of this course is a research project, which you will build up week by week.  I expect that students who put in a moderate level of effort will create a work of original research that would be appropriate for submission to a workshop or internal Tufts research symposium.  Students who put in a high level of effort and/or do some additional work on their project in the early spring can expect to produce a work of original research that would be appropriate for submission to a conference.

There will be frequent intermediate assignments related to the research project; my goal is to help you learn how to attack research and paper-writing with sustained, moderate effort rather than trying to complete the project with an intense, heroic effort shortly before the deadline.  I will provide feedback on your paper after each of these assignments; this will help you to improve both your ideas and your writing.

In addition to the project, we will be doing a lot of paper-reading in class.  To guide your reading and help you think about the papers before class, there will be short open-ended quizzes about the reading before each class. Readings will be released 1 week before the reading quiz.  The reading quiz must be completed by noon on the day of class.

How will you (and the professor) know if you are making progress in your learning?

What you get out of this class will be proportional to what you put into it.  Some things you can do to ensure that you get the most out of this opportunity are:

• Attend class: Class will be a mixture of lecture on course topics, tutorials on research, robotics, and paper-writing, and class discussion.  Participation will count for a (small) portion of your grade, and interaction with your classmates and the professor are not something that can easily be “made up” afterwards.
• Complete all paper writing assignments: You will be writing much more and earlier than you may be used to doing for research and class projects.  The schedule of intermediate assignments has been designed so that you can get feedback on your ideas at the appropriate times and so that in the last couple weeks of class you will be editing and finalizing your paper rather than doing all of the work in a panic.
• Come to open “hacking” hours: Starting 9/13, in addition to office hours, I will hold project hacking hours for a few hours each week in the CRISP lab (tentatively, Fridays 1-4pm).  This is not a formal lab, so there’s no expectation that you come the whole time or come every week, but I strongly encourage you to take advantage of this opportunity when you can, in order to get some hands-on experience with robots and get advice from the professor and your fellow students.

Office Hours & Availability

The best time to talk to me is in the weekly hacking sessions.  I will also hold office hours after class on Wednesdays.  For general questions, problems, and confusions, please post to the course Canvas page; you will rarely be the only person who is confused.  You can email me directly at elaine.short@tufts.edu for confidential questions or to set up a meeting outside of normal office hours.

In addition to the usual questions about course topics and concerns about personal issues that might be affecting your course performance, I encourage you to stop by office hours or set up a meeting to talk to me about my research, your career goals, what it’s like to work in academia, ideas for independent research projects, or thoughts you have about this course.

Names & Pronouns

If would like me to use a name or pronouns for you other than what is provided to me by the university, please feel free to let me know so that I can address you correctly.  I ask that you extend me the same courtesy and call me “Dr. Short” or “Professor Short” in class-related emails and in the classroom.

Grading:

Your grade in this class will be based on the following:

• Reading quizzes: 15%
• Research project (75% total)

• Eight interim project assignments: 5% each (40% total)
• Demo: 10%
• Final report & presentation: 25%

• Participation (10% total)

• Participating in class activities and discussions: 5%
• Leading one weeks’ reading discussion: 5%

Late work:

No late submissions will be accepted for reading quizzes, but the two lowest scores will be dropped.  Project-related assignments may be submitted up to three days late with a 5% penalty per late day, however, please be aware that submitting the assignment late will delay the feedback that you receive on that component of the project.

Tentative Schedule

The following is a tentative schedule for lecture and class activities; the topics and ordering are subject to change depending on time and students’ level of prior knowledge.

Inclusion & Accessibility

A major component of this class is class discussion and a group project.  This means you will be talking and working closely with your classmates.  I expect everyone to contribute to keeping this a professional and inclusive environment; please bring your most thoughtful selves to class and to your groups.  I expect you to adhere to a higher standard of collegiality than laid out in the relevant Tufts policies, but if necessary I will follow the steps outlined in the following:

Sexual Misconduct Policy: https://oeo.tufts.edu/policies-procedures/sexual-misconduct

Non-Discrimination Policy: https://oeo.tufts.edu/policies-procedures/non-discrimination/

Please be aware that I am a mandated reporter: if I see, hear, or hear about any kind of discrimination or sexual misconduct, I am required to report it to the university.  If you would like to access confidential counseling for an issue, you can get connected to those resources here: https://oeo.tufts.edu/care/resources/

I am also committed to creating an inclusive learning environment for students with disabilities.  Tufts suggests the following statement on accommodations:

Tufts is committed to providing equal access and support to all qualified students through the provision of reasonable accommodations so that each student may fully participate in the Tufts experience. If you have a disability that requires reasonable accommodations, please contact the Student Accessibility Services office at Accessibility@tufts.edu or 617-627-4539 to make an appointment with an SAS representative to determine appropriate accommodations. Please be aware that accommodations cannot be enacted retroactively, making timeliness a critical aspect for their provision.

You can find more information on Tufts accessibility policies and procedures here: http://students.tufts.edu/student-accessibility-services/accessibility-policies-procedures

In addition to following the standard procedures, if you have a disability and would like to discuss with me how I can better support your learning, please feel free to set up an appointment to come talk to me.

Academic Integrity

Your course project is expected to be a collaborative work of original research.  Plagiarism, including self-plagiarism, will not be tolerated.  If you are not certain what constitutes plagiarism, please consult with the resources below.  I also expect that all members of a group will contribute to the project: in cases of unequal contributions, students may have their portion of the work graded separately, or in extreme cases, have their grade lowered substantially.  Please be aware that if I find evidence of academic misconduct, I am required to report it to the university in accordance with Tufts University procedures.

You can find more information on academic integrity at Tufts here:

https://students.tufts.edu/student-affairs/student-code-conduct/academic-integrity-resources

Children in Class

All exclusively breastfeeding babies are welcome in class as often as is necessary. For older children and babies, I understand that unforseen disruptions in child-care often put parents in the position of having to choose between missing class to stay at home with a child and leaving them with someone you or the child does not feel comfortable with. While this is not meant to be a long-term child-care solution, occasionally bringing a child to class in order to cover gaps in care is perfectly acceptable.

Student Wellness

As a student, you may experience a range of challenges that can interfere with learning, such as strained relationships, increased anxiety, substance use, feeling down, difficulty of concentrating, and/or lack of motivation. These mental health concerns or stressful events may diminish your academic performance and/or reduce your ability to participate in daily activities. There are resources at Tufts to help. You can learn more about confidential health services available on campus here. For mental health emergencies, please contact the CMHS front office at 617-627-3360 during regular business hours or the counselor-on-call at 617-627-3030 after hours.

In Case of Emergency 

If you, a family member, or a close friend are experiencing an emergency or crisis: absolutely do not worry about contacting me until you have some free time. In collaboration with other university resources, we will take care of getting your course work back on track after the crisis has passed.

Acknowledgments

The course policies and course descriptions were informed by the New Computer Science Faculty Teaching Workshop, Raja Sambisavan’s COMP-150 Debugging Cloud Computing website, and Louis-Philippe Morency’s Human Communication and Machine Learning class at USC.