Deep reinforcement learning models are notoriously data hungry, yet real-world data is expensive and time consuming to obtain. The solution that many have turned to is to use simulation for training before deploying the robot in a real environment. Simulation offers the ability to train large numbers of robots in parallel, and offers an abundance of data. However, no simulation is perfect, and robots trained solely in simulation fail to generalize to the real-world, resulting in a "sim-vs-real gap". How can we overcome the trade-off between the abundance of less accurate, artificial data from simulators and the scarcity of reliable, real-world data? In this paper, we propose Bi-directional Domain Adaptation (BDA), a novel approach to bridge the sim-vs-real gap in both directions -- real2sim to bridge the visual domain gap, and sim2real to bridge the dynamics domain gap. We demonstrate the benefits of BDA on the task of PointGoal Navigation. BDA with only 5k real-world (state, action, next-state) samples matches the performance of a policy fine-tuned with ~600k samples, resulting in a speed-up of ~120x.
GUIDE: Goal-Initialized Directional Understanding for End-to-End Legged Navigation
Institute of Cyber-Systems and Control, Zhejiang University（浙江大学控制科学与工程学院）；Institute of Artificial Intelligence (TeleAI), China Telecom（中国电信人工智能研究院（TeleAI））；Oxford Robotics Institute, University of Oxford（牛津大学牛津机器人研究所）；Center for Robotics, University of Bonn（波恩大学机器人中心）；Department of Mechanical Engineering, Massachusetts Institute of Technology（麻省理工学院机械工程系）
RoomTour3D: Geometry-Aware Video-Instruction Tuning for Embodied Navigation
MBZUAI（默罕默德·本·扎耶德人工智能大学）；Shenzhen Campus of Sun Yat-Sen University（中山大学深圳校区）；AAII, UTS（悉尼科技大学人工智能与创新研究所）；University of Science and Technology of China（中国科学技术大学）
Towards Path-Creative Navigation: Robot Navigation through Embodied Interaction
School of Computer Science, Shanghai Jiao Tong University（上海交通大学计算机科学学院）；College of Information Science and Technology, Eastern Institute of Technology（东方理工大学信息科学与技术学院）；School of Mechanical and Power Engineering, Zhengzhou university（郑州大学机械与动力工程学院）；University of Waterloo（滑铁卢大学）
CausalNav: A Long-term Embodied Navigation System for Autonomous Mobile Robots in Dynamic Outdoor Scenarios
Center for Artificial Intelligence and Robotics, Shenzhen International Graduate School, Tsinghua University（人工智能与机器人中心，深圳国际研究生院，清华大学）；Peng Cheng Laboratory（鹏城实验室）
Sensing, Social, and Motion Intelligence in Embodied Navigation: A Comprehensive Survey
Shanghai Jiao Tong University（上海交通大学）；Harbin Engineering University（哈尔滨工程大学）；Tsinghua University（清华大学）；The Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学（广州））；Zhejiang University（浙江大学）
Embodied Agents Take Control: Minimal-Interface Zero-Shot Agents Rival Industrial-Scale Policies in Vision-and-Language Navigation
Australian Institute for Machine Learning（澳大利亚机器学习研究所）；Adelaide University（阿德莱德大学）；Responsible AI Research Centre（负责任人工智能研究中心）；CSIRO Data61（联邦科学与工业研究组织数据61中心）；The University of Queensland（昆士兰大学）
SpikingNav: Robust Embodied Navigation with Spiking Neural Policies
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；State Key Laboratory of Media Convergence and Communication, Communication University of China（中国传媒大学媒体融合与传播国家重点实验室）；Department of Computer Science and Technology, Tsinghua University（清华大学计算机科学与技术系）；Beijing National Research Center for Information Science and Technology, Tsinghua University（北京信息科学与技术国家研究中心）
State Key Laboratory of Robotics and Intelligent Systems（机器人与智能系统国家重点实验室）；Shenyang Institute of Automation（沈阳自动化研究所）；Chinese Academy of Sciences（中国科学院）；University of Chinese Academy of Sciences（中国科学院大学）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）
Embodied4C: Measuring What Matters for Embodied Vision-Language Navigation
Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院）；UAS Esslingen（埃森嫩大学）；TU Wien（维也纳技术大学）；Dr. Ing. h.c. F. Porsche AG（保时捷股份有限公司）；University of Michigan（密歇根大学）；Voxel51 Inc.（Voxel51公司）
Plan in Sandbox, Navigate in Open Worlds: Learning Physics-Grounded Abstracted Experience for Embodied Navigation
School of Computing and Artificial Intelligence, Southwest Jiaotong University, China（计算机与人工智能学院，西南交通大学，中国）；Centre for Frontier AI Research A*STAR, Singapore（前沿人工智能研究A*STAR中心，新加坡）；School of Computer Science, University of Leeds, UK（计算机科学学院，利兹大学，英国）
A Deployable Embodied Vision-Language Navigation System with Hierarchical Cognition and Context-Aware Exploration
Center for Advanced Robotics Technology Innovation (CARTIN), School of Electrical and Electronic Engineering, Nanyang Technological University（先进机器人技术与创新中心（CARTIN）、电子工程学院、南洋理工大学）；Spatial AI & Robotics Lab, Department of Computer Science and Engineering（空间人工智能与机器人实验室、计算机科学与工程系）
NaviTrace: Evaluating Embodied Navigation of Vision-Language Models
Robotic Systems Lab, ETH Zurich（苏黎世联邦理工学院机器人系统实验室）；Intuitive Robots Lab, KIT（卡尔斯鲁厄理工学院直观机器人实验室）；FZI Research Center for Information Technology（弗劳恩霍夫信息技术研究中心）
PM-Nav: Priori-Map Guided Embodied Navigation in Functional Buildings
Faculty of Robot Science and Engineering at Northeastern University（东北大学机器人科学与工程学院）；Foshan Graduate School of Innovation at Northeastern University（东北大学佛山创新研究生学院）；School of Aeronautic Science and Engineering at Beihang University（北航航空科学与工程学院）
A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI
Department of Computer Science, City University of Hong Kong（城市大学计算机科学系）；School of Electrical and Electronic Engineering, Nanyang Technological University（南洋理工大学电子与电气工程学院）；Department of Informatics, Universität Hamburg（汉堡大学信息学院）
