Paper Reading AI Learner

FlightGoggles: Photorealistic Sensor Simulation for Perception-driven Robotics using Photogrammetry and Virtual Reality

2019-05-27 17:59:38
Winter Guerra, Ezra Tal, Varun Murali, Gilhyun Ryou, Sertac Karaman

Abstract

FlightGoggles is a photorealistic sensor simulator for perception-driven robotic vehicles. The key contributions of FlightGoggles are twofold. First, FlightGoggles provides photorealistic exteroceptive sensor simulation using graphics assets generated with photogrammetry. Second, it also provides the ability to combine $\textit{(i)}$ synthetic exteroceptive measurements generated $\textit{in silico}$ in real time and $\textit{(ii)}$ vehicle dynamics and proprioceptive measurements generated $\textit{in motio}$ by vehicle(s) in flight in a motion-capture facility. FlightGoggles is capable of simulating a virtual-reality environment around autonomous vehicle(s) in flight. While a vehicle is in flight in the FlightGoggles virtual reality environment, exteroceptive sensors are rendered synthetically in real time while all complex extrinsic dynamics are generated organically through the natural interactions of the vehicle. The FlightGoggles framework allows for researchers to accelerate development by circumventing the need to estimate complex and hard-to-model interactions such as aerodynamics, motor mechanics, battery electrochemistry, and behavior of other agents. The ability to perform vehicle-in-the-loop experiments with photorealistic exteroceptive sensor simulation facilitates novel research directions involving, $\textit{e.g.}$, fast and agile autonomous flight in obstacle-rich environments, safe human interaction, and flexible sensor selection. FlightGoggles has been utilized as the main test for selecting nine teams that will advance in the AlphaPilot autonomous drone racing challenge. Subsequently, FlightGoggles has been actively used by the community. We survey approaches and results from the top twenty AlphaPilot teams, which may be of independent interest.

Abstract (translated)

FlightGoggles是一种用于感知驱动机器人车辆的真实感传感器模拟器。护目镜的主要作用是双重的。首先,FlightGoggles使用摄影测量生成的图形资源提供了真实的外部探测传感器模拟。其次,它还提供了将实时生成的$ extit(i)$synthetic extroceptive measurements generated$ extit和实时生成的$ extit(ii)$vehicle dynamics和运动捕获设备中飞行车辆生成的$ extit$飞行护目镜能够模拟飞行中自主飞行器周围的虚拟现实环境。当飞行器在护目镜虚拟现实环境中飞行时,外部传感器是实时综合渲染的,而所有复杂的外部动力学都是通过飞行器的自然相互作用有机生成的。FlightGoggles框架允许研究人员通过规避评估复杂和难以建模的相互作用(如空气动力学、电机力学、电池电化学和其他因素的行为)的需要来加速发展。利用真实感外处理传感器模拟进行车辆在环试验的能力有助于实现新的研究方向,包括:$ extit,例如:$;在障碍物丰富的环境中快速灵活的自主飞行、安全的人与人的交互以及灵活的传感器选择。飞行护目镜已被用来作为主要测试,选择九个小组,将在阿尔法匹洛特自主无人机竞赛挑战前进。随后,护目镜被社会广泛使用。我们调查的方法和结果来自前20个阿尔法pilot团队,这可能是独立的兴趣。

URL

https://arxiv.org/abs/1905.11377

PDF

https://arxiv.org/pdf/1905.11377.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