6 papers
FAM-HRI: Foundation-Model Assisted Multi-Modal Human-Robot Interaction Combining Gaze and Speech
Yuzhi Lai, Shenghai Yuan, Peizheng Li +4
ffective Human-Robot Interaction (HRI) is crucial for enhancing accessibility and usability in real-world robotics applications. However, existing solutions often rely on gesture-…
SEER-VAR: Semantic Egocentric Environment Reasoner for Vehicle Augmented Reality
Yuzhi Lai, Shenghai Yuan, Peizheng Li +2
We present SEER-VAR, a novel framework for egocentric vehicle-based augmented reality (AR) that unifies semantic decomposition, Context-Aware SLAM Branches (CASB), and LLM-driven r…
UAVScenes: A Multi-Modal Dataset for UAVs
Sijie Wang, Siqi Li, Yawei Zhang +16
Multi-modal perception is essential for unmanned aerial vehicle (UAV) operations, as it enables a comprehensive understanding of the UAVs' surrounding environment. However, most ex…
Tire Wear Aware Trajectory Tracking Control for Multi-axle Swerve-drive Autonomous Mobile Robots
Tianxin Hu, Xinhang Xu, Thien-Minh Nguyen +3
Multi-axle Swerve-drive Autonomous Mobile Robots (MS-AGVs) equipped with independently steerable wheels are commonly used for high-payload transportation. In this work, we present…
Natural Multimodal Fusion-Based Human-Robot Interaction: Application With Voice and Deictic Posture via Large Language Model
Yuzhi Lai, Shenghai Yuan, Youssef Nassar +5
Translating human intent into robot commands is crucial for the future of service robots in an aging society. Existing Human-Robot Interaction (HRI) systems relying on gestures or…
NVP-HRI: Zero Shot Natural Voice and Posture-based Human-Robot Interaction via Large Language Model
Yuzhi Lai, Shenghai Yuan, Youssef Nassar +3
Effective Human-Robot Interaction (HRI) is crucial for future service robots in aging societies. Existing solutions are biased toward only well-trained objects, creating a gap when…