This paper introduces mathematical models of \sensors\ for mobile robots based on visibility. Serving a purpose similar to the pinhole camera model for computer vision, the introduced models are expected to provide a useful, idealized characterization of task-relevant information that can be inferred from their outputs or observations. Possible tasks include navigation, localization and mapping when a mobile robot is deployed in an unknown environment. These models allow direct comparisons to be made between traditional depth sensors, highlighting cases in which touch sensing may be interchangeable with time of flight or vision sensors, and characterizing unique advantages provided by touch sensing. The models include contact detection, compression, load bearing, and deflection. The results could serve as a basic building block for innovative touch sensor designs for mobile robot sensor fusion systems.
University of Electronic Science and Technology of China（电子科技大学）；Dartmouth College（达特茅斯学院）
Underwater navigation presents several challenges, including unstructured unknown environments, lack of reliable localization systems (e.g., GPS), and poor visibility. Furthermore, good-quality obstacle detection sensors for underwater robots are scant and costly; and many sensors like RGB-D cameras and LiDAR only work in-air. To enable reliable mapless underwater navigation despite these challenges, we propose a low-cost end-to-end navigation system, based on a monocular camera and a fixed single-beam echo-sounder, that efficiently navigates an underwater robot to waypoints while avoiding nea…
Visual monitoring operations underwater require both observing the objects of interest in close-proximity, and tracking the few feature-rich areas necessary for state estimation.This paper introduces the first navigation framework, called AquaVis, that produces on-line visibility-aware motion plans that enable Autonomous Underwater Vehicles (AUVs) to track multiple visual objectives with an arbitrary camera configuration in real-time. Using the proposed pipeline, AUVs can efficiently move in 3D, reach their goals while avoiding obstacles safely, and maximizing the visibility of multiple object…
This paper presents an autonomous navigation system for ground robots traversing aggressive unstructured terrain through a cohesive arrangement of mapping, deliberative planning and reactive behaviour modules. All systems are aware of terrain slope, visibility and vehicle orientation, enabling robots to recognize, plan and react around unobserved areas and overcome negative obstacles, slopes, steps, overhangs and narrow passageways. This is one of pioneer works to explicitly and simultaneously couple mapping, planning and reactive components in dealing with negative obstacles. The system was d…
A Robust Simulation Framework for Verification and Validation of Autonomous Maritime Navigation in Adverse Weather and Constrained Environments
Department of Mechanical Engineering, Texas A&M University, College Station, USA（机械工程系，德克萨斯A&M大学，学院站，美国）；Department of Ocean Engineering, Texas A&M University, College Station, USA（海洋工程系，德克萨斯A&M大学，学院站，美国）；American Bureau of Shipping, Spring, TX, USA（美国船舶局，斯普林，德克萨斯州，美国）
Inverse k-visibility for RSSI-based Indoor Geometric Mapping
Department of Cognitive Robotics, Delft University of Technology（认知机器人系，代尔夫特理工大学）；Department of Mechanical and Industrial Engineering, University of Toronto（机械与工业工程系，多伦多大学）；Department of Computer Science, Toronto Metropolitan University（计算机科学系，多伦多 Metropolitan 大学）；Department of Computer Science, University College London（计算机科学系，伦敦大学学院）
Beijing Institute of Technology（北京理工大学）；Beijing Lab of Intelligent Information Technology（北京智能信息技术实验室）
This paper presents the architecture and implementation of a tele-presence wheelchair system based on tele-presence robot, intelligent wheelchair, and touch screen technologies. The tele-presence wheelchair system consists of a commercial electric wheelchair, an add-on tele-presence interaction module, and a touchable live video image based user interface (called TIUI). The tele-presence interaction module is used to provide video-chatting for an elderly or disabled person with the family members or caregivers, and also captures the live video of an environment for tele-operation and semi-auto…
Oxford Robotics Institute, University of Oxford（牛津大学牛津机器人研究所）；Institute of Robotics and Machine Intelligence, Poznan University of Technology（波兹南理工大学机器人与机器智能研究所）
Legged robot navigation in extreme environments can hinder the use of cameras and laser scanners due to darkness, air obfuscation or sensor damage. In these conditions, proprioceptive sensing will continue to work reliably. In this paper, we propose a purely proprioceptive localization algorithm which fuses information from both geometry and terrain class, to localize a legged robot within a prior map. First, a terrain classifier computes the probability that a foot has stepped on a particular terrain class from sensed foot forces. Then, a Monte Carlo-based estimator fuses this terrain class p…
Robust navigation in urban environments has received a considerable amount of both academic and commercial interest over recent years. This is primarily due to large commercial organizations such as Google and Uber stepping into the autonomous navigation market. Most of this research has shied away from Global Navigation Satellite System (GNSS) based navigation. The aversion to utilizing GNSS data is due to the degraded nature of the data in urban environment (e.g., multipath, poor satellite visibility). The degradation of the GNSS data in urban environments makes it such that traditional (GNS…
In this paper, we examine the problem of visibility-aware robot navigation among movable obstacles (VANAMO). A variant of the well-known NAMO robotic planning problem, VANAMO puts additional visibility constraints on robot motion and object movability. This new problem formulation lifts the restrictive assumption that the map is fully visible and the object positions are fully known. We provide a formal definition of the VANAMO problem and propose the Look and Manipulate Backchaining (LaMB) algorithm for solving such problems. LaMB has a simple vision-based API that makes it more easily transf…
Coordinated Multi-Robot Navigation with Formation Adaptation
University of Massachusetts Amherst（马萨诸塞大学阿默斯特分校）；North Carolina State University（北卡罗来纳州立大学）；University of Denver（丹佛大学）；U.S. Army DEVCOM Army Research Laboratory (ARL)（美国陆军DEVCOM陆军研究实验室）
Deep Learning-based Robust Autonomous Navigation of Aerial Robots in Dense Forests
Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute FGI, The National Land Survey of Finland（遥感与摄影测量系，芬兰地理空间研究 institute FGI，芬兰国家土地测绘局）
OPAL: Visibility-aware LiDAR-to-OpenStreetMap Place Recognition via Adaptive Radial Fusion
Technical University of Munich（慕尼黑技术大学）；Wuhan University（武汉大学）；University of Science and Technology of China（中国科学技术大学）；University of Cambridge（剑桥大学）；Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院）
RAVEN: Reinforcement-Adaptive Visibility-Graph Planning for Robust Humanoid Navigation with Collision-Free MPC
Robotics and Mechanisms Laboratory (RoMeLa), Department of Mechanical and Aerospace Engineering, University of California, Los Angeles（机器人与机构实验室（RoMeLa），机械与航天工程系，加利福尼亚大学洛杉矶分校）
Realm: Real-Time Line-of-Sight Maintenance in Multi-Robot Navigation with Unknown Obstacles
School of Electrical and Electronic Engineering, Nanyang Technological University（南洋理工大学电气与电子工程学院）；Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR)（新加坡科技研究局信息通信研究所）；School of Automation, Chongqing University（重庆大学自动化学院）；College of Computer Science, Sichuan University（四川大学计算机学院）
Beyond Visibility Limits: A DRL-Based Navigation Strategy for Unexpected Obstacles
Eastern Institute of Technology（东方理工学院）；Hong Kong Polytechnic University（香港理工大学）；National University of Singapore（新加坡国立大学）；Harbin Institute of Technology, Shenzhen（哈尔滨工业大学（深圳））
With an ever-widening domain of aerial robotic applications, including many mission critical tasks such as disaster response operations, search and rescue missions and infrastructure inspections taking place in GPS-denied environments, the need for reliable autonomous operation of aerial robots has become crucial. Operating in GPS-denied areas aerial robots rely on a multitude of sensors to localize and navigate. Visible spectrum cameras are the most commonly used sensors due to their low cost and weight. However, in environments that are visually-degraded such as in conditions of poor illumin…
The problem of path planning in unknown environments remains a challenging problem - as the environment is gradually observed during the navigation, the underlying planner has to update the environment representation and replan, promptly and constantly, to account for the new observations. In this paper, we present a visibility graph-based planning framework capable of dealing with navigation tasks in both known and unknown environments. The planner employs a polygonal representation of the environment and constructs the representation by extracting edge points around obstacles to form enclose…
Università di Pisa（比萨大学）；University of Ottawa（渥太华大学）
In this paper we study the Near-Gathering problem for a finite set of dimensionless, deterministic, asynchronous, anonymous, oblivious and autonomous mobile robots with limited visibility moving in the Euclidean plane in Look-Compute-Move (LCM) cycles. In this problem, the robots have to get close enough to each other, so that every robot can see all the others, without touching (i.e., colliding with) any other robot. The importance of solving the Near-Gathering problem is that it makes it possible to overcome the restriction of having robots with limited visibility. Hence it allows to exploit…
From Region Arrival to Instance-Level Grounding in Vision-and-Language Navigation
Australian Institute for Machine Learning, Adelaide University（澳大利亚机器学习研究所，阿德莱德大学）；Ruyi Dynamics（如意动力）；Fudan University（复旦大学）；Swiss Federal Institute of Technology Lausanne (EPFL)（瑞士洛桑联邦理工学院）
In the context of autonomous driving, vehicles are inherently bound to encounter more extreme weather during which public safety must be ensured. As climate is quickly changing, the frequency of heavy snowstorms is expected to increase and become a major threat to safe navigation. While there is much literature aiming to improve navigation resiliency to winter conditions, there is a lack of standard metrics to quantify the loss of visibility of lidar sensors related to precipitation. This chapter proposes a novel metric to quantify the lidar visibility loss in real time, relying on the notion …
Visibility underwater is challenging, and degrades as the distance between the subject and camera increases, making vision tasks in the forward-looking direction more difficult. We have collected underwater forward-looking stereo-vision and visual-inertial image sets in the Mediterranean and Red Sea. To our knowledge there are no other public datasets in the underwater environment acquired with this camera-sensor orientation published with ground-truth. These datasets are critical for the development of several underwater applications, including obstacle avoidance, visual odometry, 3D tracking…
To help future mobile agents plan their movement in harsh environments,a predictive model has been designed to determine what areas would be favorable for Global Navigation Satellite System (GNSS) positioning. The model is able to predict the number of viable satellites for a GNSS receiver, based on a 3D point cloud map and a satellite constellation. Both occlusion and absorption effects of the environment are considered. A rugged mobile platform was designed to collect data in order to generate the point cloud maps. It was deployed during the Canadian winter known for large amounts of snow an…
Fraunhofer Institute for Communication, Information Processing and Ergonomics FKIE（弗劳恩霍夫通信、信息处理与工效学研究所FKIE）；University of Bonn（波恩大学）
Safe navigation of Micro Aerial Vehicles (MAVs) requires not only obstacle-free flight paths according to a static environment map, but also the perception of and reaction to previously unknown and dynamic objects. This implies that the onboard sensors cover the current flight direction. Due to the limited payload of MAVs, full sensor coverage of the environment has to be traded off with flight time. Thus, often only a part of the environment is covered. We present a combined allocentric complete planning and trajectory optimization approach taking these sensor visibility constraints into acco…
Nanyang Technological University（南洋理工大学）；Institute for Infocomm Research, Agency for Science, Technology and Research（新加坡科技研究局资讯通信研究院）
Tactile sensors have been introduced to a wide range of robotic tasks such as robot manipulation to mimic the sense of human touch. However, there has only been a few works that integrate tactile sensing into robot navigation. This paper describes a navigation system which allows robots to operate in crowded human-dense environments and behave with socially acceptable reactions by utilizing semantic and force information collected by embedded tactile sensors, RGB-D camera and LiDAR. Compliance control is implemented based on artificial potential fields considering not only laser scan but also …
SHRUMS: Sensor Hallucination for Real-time Underwater Motion Planning with a Compact 3D Sonar
Department of Computer Science and Engineering, Texas A&M University（计算机科学与工程系，德克萨斯A&M大学）；Aquaculture Robotics and Automation, SINTEF Ocean（水产养殖机器人与自动化，SINTEF海洋）
Sapienza University of Rome（罗马大学）；IT+Robotics S.r.l.（IT+Robotics有限公司）
This work addresses the problem of coupling vision-based navigation systems for Unmanned Aerial Vehicles (UAVs) with robust obstacle avoidance capabilities. The former problem is solved by maximizing the visibility of the points of interest, while the latter is modeled by means of ellipsoidal repulsive areas. The whole problem is transcribed into an Optimal Control Problem (OCP), and solved in a few milliseconds by leveraging state-of-the-art numerical optimization. The resulting trajectories are well suited for reaching the specified goal location while avoiding obstacles with a safety margin…
CosFly-Track: A Large-Scale Multi-Modal Dataset for UAV Visual Tracking via Multi-Constraint Trajectory Optimization
Autel Robotics（Autel机器人公司）；Nanjing University（南京大学）；Peking University（北京大学）；Southern University of Science and Technology（南方科技大学）；University of Hong Kong（香港大学）
