Dances with robots (with Catie Cuan)

Jul 21, 2021 1h 7m 14 insights Episode Page ↗
Spencer Greenberg speaks with Katie Kwan, a PhD in mechanical engineering, about her unique path combining dance and robotics. They explore how dance principles inform robot motion design, the future of human-robot interaction in VR and daily life, and the collaborative role of humans in AI-generated art.
Actionable Insights

1. Prioritize Human-Centric Robot Motion

When designing robots that interact with people, prioritize motion that considers psychological factors like comfort, empowerment, and friendliness over mere efficiency, because motion profoundly impacts human perception and interaction.

2. Integrate Choreographic Language

Roboticists should learn from dancers’ extensive vocabulary for describing and creating motion (e.g., repetition, inversion, transformation, canon, space holds) to explore a wider, more experimental design space beyond optimal trajectories.

3. Dancers: Expand Skill Sets

Dancers should learn programming, sensor technology, and robot motion planning to apply their expertise in new contexts like robot personality design or interaction modes for wearables, moving beyond the traditional stage.

4. Embrace Dance for Social Bonds

Engage in dance, regardless of perceived skill or sanctioned spaces, because it is a foundational human activity that codifies social bonds and interbehavioral group dynamics.

5. Combine Disparate Interests

Pursue parallel interests, even if they seem unrelated, as combining them (e.g., dance and technology) can lead to unique, fulfilling career paths and innovative interdisciplinary work.

6. Implement Human-in-the-Loop Systems

Design AI and robotics systems with a “human in the loop” where human operators can intervene when the system is uncertain or stuck, and their input helps train and improve the algorithm over time. This balances automation with human oversight and expertise.

7. AI as Collaborative Tool

Recognize that AI, especially in creative fields, functions as a tool for human collaboration rather than an autonomous artist; humans define training data, tune parameters, and make artistic choices, fundamentally shaping the output.

8. Train Robots with VR/Simulation

Utilize virtual reality and simulation platforms to efficiently train robots by having them practice tasks with vast amounts of simulated data, which can then be transferred to real-world robots, allowing for rapid learning and testing.

9. Leverage VR for Empathy

Use virtual reality systems to simulate inhabiting different bodies (human or robot) to foster empathy and understanding of diverse experiences, as demonstrated by projects like the “Be Another Lab.”

10. Experiment with “Ugly” Motion

Roboticists should consider exploring “ugly,” chaotic, or disorienting types of motion, similar to how dancers do, to expand the design space beyond purely optimal or aesthetically pleasing movements.

11. Explore Creative Feedback Loops

Create interactive systems where human and robot actions continuously feed into each other, allowing for organic, emergent motion and a commentary on societal interactions with technology, as exemplified by “The Loop” project.

12. Develop Niche Consumer Robots

Consider developing consumer robots for specific, high-value niche applications like elder care (e.g., companion robots, mobility assistance, automated food preparation) where the benefits clearly outweigh the cost and complexity.

13. Anticipate Robot Failures

When performing or demonstrating with robots, be prepared for frequent breakdowns due to software bugs, hardware malfunctions, or connectivity issues, as these are common and can dramatically alter the intended meaning of a piece.

14. Understand Robust Robotics Cost

Recognize that achieving 99.9% robust and reliable performance for robots in diverse, real-world conditions is extremely challenging and expensive, which currently limits their widespread consumer adoption.