Kiri-Spoon: A Soft Shape-Changing Utensil for Robot-Assisted Feeding (2403.05784v1)
Abstract: Assistive robot arms have the potential to help disabled or elderly adults eat everyday meals without relying on a caregiver. To provide meaningful assistance, these robots must reach for food items, pick them up, and then carry them to the human's mouth. Current work equips robot arms with standard utensils (e.g., forks and spoons). But -- although these utensils are intuitive for humans -- they are not easy for robots to control. If the robot arm does not carefully and precisely orchestrate its motion, food items may fall out of a spoon or slide off of the fork. Accordingly, in this paper we design, model, and test Kiri-Spoon, a novel utensil specifically intended for robot-assisted feeding. Kiri-Spoon combines the familiar shape of traditional utensils with the capabilities of soft grippers. By actuating a kirigami structure the robot can rapidly adjust the curvature of Kiri-Spoon: at one extreme the utensil wraps around food items to make them easier for the robot to pick up and carry, and at the other extreme the utensil returns to a typical spoon shape so that human users can easily take a bite of food. Our studies with able-bodied human operators suggest that robot arms equipped with Kiri-Spoon carry foods more robustly than when leveraging traditional utensils. See videos here: https://youtu.be/nddAniZLFPk
- B. D. Argall, “Autonomy in rehabilitation robotics: An intersection,” Annual Review of Control, Robotics, and Autonomous Systems, vol. 1, pp. 441–463, 2018.
- A. Nanavati, P. Alves-Oliveira, T. Schrenk, E. K. Gordon, M. Cakmak, and S. S. Srinivasa, “Design principles for robot-assisted feeding in social contexts,” in ACM/IEEE International Conference on Human-Robot Interaction, 2023, pp. 24–33.
- E. K. Gordon, A. Nanavati, R. Challa, B. H. Zhu, T. A. K. Faulkner, and S. Srinivasa, “Towards general single-utensil food acquisition with human-informed actions,” in Conference on Robot Learning, 2023, pp. 2414–2428.
- D. Park, Y. Hoshi, H. P. Mahajan, H. K. Kim, Z. Erickson, W. A. Rogers, and C. C. Kemp, “Active robot-assisted feeding with a general-purpose mobile manipulator: Design, evaluation, and lessons learned,” Robotics and Autonomous Systems, vol. 124, p. 103344, 2020.
- D. P. Losey, H. J. Jeon, M. Li, K. Srinivasan, A. Mandlekar, A. Garg, J. Bohg, and D. Sadigh, “Learning latent actions to control assistive robots,” Autonomous Robots, vol. 46, no. 1, pp. 115–147, 2022.
- J. Ondras, A. Anwar, T. Wu, F. Bu, M. Jung, J. J. Ortiz, and T. Bhattacharjee, “Human-robot commensality: Bite timing prediction for robot-assisted feeding in groups,” in Conference on Robot Learning, 2023, pp. 921–933.
- J. R. Schultz, A. B. Slifkin, H. Yu, and E. M. Schearer, “Proof-of-concept: A hands-free interface for robot-assisted self-feeding,” in International Conference on Rehabilitation Robotics, 2022.
- R. Feng, Y. Kim, G. Lee, E. K. Gordon, M. Schmittle, S. Kumar, T. Bhattacharjee, and S. S. Srinivasa, “Robot-assisted feeding: Generalizing skewering strategies across food items on a plate,” in The International Symposium of Robotics Research, 2019, pp. 427–442.
- S. Belkhale, E. K. Gordon, Y. Chen, S. Srinivasa, T. Bhattacharjee, and D. Sadigh, “Balancing efficiency and comfort in robot-assisted bite transfer,” in IEEE International Conference on Robotics and Automation, 2022, pp. 4757–4763.
- J. Shintake, V. Cacucciolo, D. Floreano, and H. Shea, “Soft robotic grippers,” Advanced Materials, vol. 30, no. 29, 2018.
- Z. Wang, S. Hirai, and S. Kawamura, “Challenges and opportunities in robotic food handling: A review,” Frontiers in Robotics and AI, vol. 8, p. 789107, 2022.
- S. A. Mehta, Y. Kim, J. Hoegerman, M. D. Bartlett, and D. P. Losey, “RISO: Combining rigid grippers with soft switchable adhesives,” in IEEE International Conference on Soft Robotics, 2023.
- A. Gafer, D. Heymans, D. Prattichizzo, and G. Salvietti, “The quad-spatula gripper: A novel soft-rigid gripper for food handling,” in IEEE International Conference on Soft Robotics, 2020, pp. 39–45.
- J. Zhu, Z. Chai, H. Yong, Y. Xu, C. Guo, H. Ding, and Z. Wu, “Bioinspired multimodal multipose hybrid fingers for wide-range force, compliant, and stable grasping,” Soft Robotics, vol. 10, no. 1, pp. 30–39, 2023.
- W. Ruotolo, D. Brouwer, and M. R. Cutkosky, “From grasping to manipulation with gecko-inspired adhesives on a multifinger gripper,” Science Robotics, vol. 6, no. 61, p. eabi9773, 2021.
- D. J. Rea and S. H. Seo, “Still not solved: A call for renewed focus on user-centered teleoperation interfaces,” Frontiers in Robotics and AI, vol. 9, p. 704225, 2022.
- T. Bhattacharjee, E. K. Gordon, R. Scalise, M. E. Cabrera, A. Caspi, M. Cakmak, and S. S. Srinivasa, “Is more autonomy always better? Exploring preferences of users with mobility impairments in robot-assisted feeding,” in ACM/IEEE International Conference on Human-Robot Interaction, 2020, pp. 181–190.
- P. Sundaresan, S. Belkhale, and D. Sadigh, “Learning visuo-haptic skewering strategies for robot-assisted feeding,” in Conference on Robot Learning, 2023, pp. 332–341.
- L. Shaikewitz, Y. Wu, S. Belkhale, J. Grannen, P. Sundaresan, and D. Sadigh, “In-mouth robotic bite transfer with visual and haptic sensing,” in IEEE International Conference on Robotics and Automation, 2023, pp. 9885–9895.
- J. Grannen, Y. Wu, S. Belkhale, and D. Sadigh, “Learning bimanual scooping policies for food acquisition,” in Conference on Robot Learning, 2022.
- Y. Hong, Y. Chi, S. Wu, Y. Li, Y. Zhu, and J. Yin, “Boundary curvature guided programmable shape-morphing kirigami sheets,” Nature Communications, vol. 13, no. 1, p. 530, 2022.