Paper Reading AI Learner

Using Infant Limb Movement Data to Control Small Aerial Robots

2022-08-11 08:46:45
Georgia Kouvoutsakis, Elena Kokkoni, Konstantinos Karydis

Abstract

Promoting exploratory movements through contingent feedback can positively influence motor development in infancy. Our ongoing work gears toward the development of a robot-assisted contingency learning environment through the use of small aerial robots. This paper examines whether aerial robots and their associated motion controllers can be used to achieve efficient and highly-responsive robot flight for our purpose. Infant kicking kinematic data were extracted from videos and used in simulation and physical experiments with an aerial robot. The efficacy of two standard of practice controllers was assessed: a linear PID and a nonlinear geometric controller. The ability of the robot to match infant kicking trajectories was evaluated qualitatively and quantitatively via the mean squared error (to assess overall deviation from the input infant leg trajectory signals), and dynamic time warping algorithm (to quantify the signal synchrony). Results demonstrate that it is in principle possible to track infant kicking trajectories with small aerials robots, and identify areas of further development required to improve the tracking quality.

Abstract (translated)

URL

https://arxiv.org/abs/2208.05698

PDF

https://arxiv.org/pdf/2208.05698.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 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 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 Tracking Transfer_Learning Transformer Unsupervised Video_Caption Video_Classification Video_Indexing Video_Prediction Video_Retrieval Visual_Relation VQA Weakly_Supervised Zero-Shot