David Crandall

About

David Crandall’s research lies at the intersection of human-robot interaction, computer vision, and assistive technology, with a particular focus on supporting older adults through socially aware robotics. His most impactful work, “Spill the Tea” (32 citations), demonstrates how autonomous social robots can engage older adults in meaningful conversations to reflect on and improve their well-being, pioneering a new approach to robotic companionship. Crandall has also advanced technical frontiers, including cloud-based SLAM for mobile robots (20 citations), which reduces onboard computational demands, and gesture forecasting for human-drone interaction (12 citations), enabling more intuitive control. His longitudinal co-design studies (11 citations) reveal how older adults learn and contribute to robot design over time, while his work on ikigai reflection (9 citations) helps users rediscover purpose through robot-guided dialogue. Crandall’s contributions extend to end-user robot programming, empowering non-experts to create custom interactions, and cross-cultural studies on robot voice perception among older adults in the U.S. and Japan. With over 125 total citations across his top papers, Crandall is shaping a future where robots are not just functional tools but empathetic partners in aging and daily life.

Research Focus

Key Achievements

Top Papers

1. 1
   Spill the Tea

   32 citations · 2023
2. 2
   Cloud-based Parallel Implementation of SLAM for Mobile Robots

   20 citations · 2016
3. 3
   Bittersweet Snapshots of Life: Designing to Address Complex Emotions in a Reminiscence Interaction between Older Adults and a Robot

   14 citations · 2025
4. 4
   Forecasting Hand Gestures for Human-Drone Interaction

   12 citations · 2018
5. 5
   "Give it Time:" Longitudinal Panels Scaffold Older Adults' Learning and Robot Co-Design

   11 citations · 2024
6. 6
   Let’s Talk About You: Development and Evaluation of an Autonomous Robot to Support Ikigai Reflection in Older Adults

   9 citations · 2024
7. 7
   Few-Shot Segmentation and Semantic Segmentation for Underwater Imagery

   7 citations · 2023
8. 8
   If [YourName] Can Code, So Can You! End-User Robot Programming For Non-Experts

   7 citations · 2024
9. 9
   Automatic Annotation for Semantic Segmentation in Indoor Scenes

   7 citations · 2019
10. 10
    Finding its Voice: The Influence of Robot Voice on Fit, Social Attributes, and Willingness to Use Among Older Adults in the U.S. and Japan

    6 citations · 2023

Key Collaborators

Contact & Links