Paper Reading AI Learner

OAA: Three Phases of Vocal Guidance in Human-Drone Teleoperation

2026-08-11 08:35:08
Allan Henry (LPNC, GIPSA-COPERNIC, LIG, GETALP), Christian Graff (LPNC), Solange Rossato (LIG, GETALP), Jos\'e-Ernesto Gomez-Balderas (GIPSA-COPERNIC), Sylvain Huet (GIPSA-COPERNIC)

Abstract

Voice-guided teleoperation requires systems that adapt to the evolving dynamics of human guidance. Yet most voice-controlled robot systems treat spoken commands as a stationary stream, ignoring how the guide's communicative behavior changes as the task progresses. Using motion capture and speech data from two experimental configurations, humanhuman guidance (finger pointing, N =10 dyads) and humandrone teleoperation (gamepad control, N =29 dyads), we show that spontaneous vocal guidance consistently organizes into three kinematically and linguistically distinct phases: Orientation, Approach, and Adjustment. These phases are identified automatically via change point detection on 3D trajectory signals, and validated statistically (Kruskal-Wallis, p<.001). Three lexical families replicate across configurations: rotation vocabulary marks Orientation, translation vocabulary is scarce there, and attenuators accumulate toward Adjustment. Together with inter-utterance silence, these cues mark the Orientation boundary that speech rate alone leaves unmarked. The same three-phase structure emerges in both configurations despite radically different motor interfaces, suggesting it is an intrinsic property of human spatial guidance rather than an artifact of the experimental setup. We discuss implications for OAA-aware adaptive control in voice-guided teleoperation.

Abstract (translated)

URL

https://arxiv.org/abs/2608.10651

PDF

https://arxiv.org/pdf/2608.10651.pdf


Tags
3D Action Action_Localization Action_Recognition Activity Adversarial Agent Attention Autonomous Bert Boundary_Detection Caption Chat Classification CNN Compressive_Sensing Contour Contrastive_Learning Deep_Learning Denoising Detection Dialog Diffusion Drone Dynamic_Memory_Network Edge_Detection Embedding Embodied Emotion Enhancement Face Face_Detection Face_Recognition Facial_Landmark Few-Shot Gait_Recognition GAN Gaze_Estimation Gesture Gradient_Descent Handwriting Human_Parsing Image_Caption Image_Classification Image_Compression Image_Enhancement Image_Generation Image_Matting Image_Retrieval Inference Inpainting Intelligent_Chip Knowledge Knowledge_Graph Language_Model LLM Matching Medical Memory_Networks Multi_Modal Multi_Task NAS NMT Object_Detection Object_Tracking OCR Ontology Optical_Character Optical_Flow Optimization Person_Re-identification Point_Cloud Portrait_Generation Pose Pose_Estimation Prediction QA Quantitative Quantitative_Finance Quantization Re-identification Recognition Recommendation Reconstruction Regularization Reinforcement_Learning Relation Relation_Extraction Represenation Represenation_Learning Restoration Review RNN Robot Salient Scene_Classification Scene_Generation Scene_Parsing Scene_Text Segmentation Self-Supervised Semantic_Instance_Segmentation Semantic_Segmentation Semi_Global Semi_Supervised Sence_graph Sentiment Sentiment_Classification Sketch SLAM Sparse Speech Speech_Recognition Style_Transfer Summarization Super_Resolution Surveillance Survey Text_Classification Text_Generation Time_Series Tracking Transfer_Learning Transformer Unsupervised Video_Caption Video_Classification Video_Indexing Video_Prediction Video_Retrieval Visual_Relation VQA Weakly_Supervised Zero-Shot