4 papers
Beyond Human-Derived Motion: Exploring Robot-Specific Execution for Construction Humanoids
MinJun Chang, Taehyung Kim, Yong K. Cho +1
Construction productivity has remained a per- sistent challenge, motivating growing interest in humanoid robots that can operate in workspaces and with tools designed for human wor…
Collision Snapshot Guided Time-Reversed Safety-Critical Scenario Generation
Taehyung Kim, Jongeun Choi
The generation of safety-critical traffic scenarios is essential for training and evaluating autonomous vehicles. Prior approaches typically perturb the trajectories of existing ag…
To Go Far, Go Together: Diverse Preferences Induce a Curriculum for Reward Optimization
Taehyung Kim, Jongeun Choi
Learning a reward model from human feedback and optimizing a policy against it is one approach to aligning AI systems with individual users. From a fairness perspective, existing w…
Deployable Human Preference Alignment in Robotics: Learning Representative Rewards from Diverse Human Preferences
Taehyung Kim, Gwangmo Lee, Minjun Chang +2
Aligning robot policies with human preferences is essential for deployment to diverse end users. In per-user alignment approach, preference feedback is often sparse, so learning be…