Context-Continuous Preference Learning for Exoskeleton Personalization
Personalizing exoskeleton assistance across operating conditions is constrained by the time and physical effort required to collect user feedback. We examined whether a user's preference landscape varies smoothly across operating conditions and when this continuity supports learning from limited feedback. We propose Context-Continuous Preference Learning (CCPL), a Gaussian-process preference model that shares observations across nearby contexts while retaining context-specific utility estimates. We evaluated CCPL through simulations and retrospective analyses of ankle and elbow exoskeleton preference data from nine healthy adults. In simulations, CCPL improved reconstruction and preferenc...
| Authors | Sunin Baek, Sungwoo Park, Daekyum Kim |
|---|---|
| Primary category | cs.LG |
| Published | 23 September 2026 |
| Last updated at source | 23 September 2026 |
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