This study develops a robot mobility policy based on deep reinforcement learning. Since traditional methods of conventional robotic navigation depend on accurate map reproduction as well as require high-end sensors, learning-based methods are positive trends, especially deep reinforcement learning. The problem is modeled in the form of a Markov Decision Process (MDP) with the agent being a mobile robot. Its state of view is obtained by the input sensors such as laser findings or cameras and the purpose is navigating to the goal without any collision. There have been many deep learning methods that solve this problem. However, in order to bring robots to market, low-cost mass production is also an issue that needs to be addressed. Therefore, this work attempts to construct a pseudo laser findings system based on direct depth matrix prediction from a single camera image while still retaining stable performances. Experiment results show that they are directly comparable with others using high-priced sensors.
University of Surrey（萨里大学）；UK Atomic Energy Authority（英国原子能管理局）
Driving energy consumption plays a major role in the navigation of mobile robots in challenging environments, especially if they are left to operate unattended under limited on-board power. This paper reports on first results of an energy-aware path planner, which can provide estimates of the driving energy consumption and energy recovery of a robot traversing complex uneven terrains. Energy is estimated over trajectories making use of a self-supervised learning approach, in which the robot autonomously learns how to correlate perceived terrain point clouds to energy consumption and recovery. …
City University of Hong Kong（香港城市大学）；HKUST（香港科技大学）；ETH Zurich（苏黎世联邦理工学院）
We present a learning-based mapless motion planner by taking the sparse 10-dimensional range findings and the target position with respect to the mobile robot coordinate frame as input and the continuous steering commands as output. Traditional motion planners for mobile ground robots with a laser range sensor mostly depend on the obstacle map of the navigation environment where both the highly precise laser sensor and the obstacle map building work of the environment are indispensable. We show that, through an asynchronous deep reinforcement learning method, a mapless motion planner can be tr…
KTH Royal Institute of Technology（瑞典皇家理工学院）；Purdue University（普渡大学）；Sapienza University of Rome（罗马大学）
Mobile robots, be it autonomous or teleoperated, require stable communication with the base station to exchange valuable information. Given the stochastic elements in radio signal propagation, such as shadowing and fading, and the possibilities of unpredictable events or hardware failures, communication loss often presents a significant mission risk, both in terms of probability and impact, especially in Urban Search and Rescue (USAR) operations. Depending on the circumstances, disconnected robots are either abandoned or attempt to autonomously back-trace their way to the base station. Althoug…
College of Electronics and Information Engineering, Tongji University（同济大学电子与信息工程学院）；School of Cyber Science and Engineering, Southeast University（东南大学网络空间安全学院）；School of Automation, Southeast University（东南大学自动化学院）
In this paper, a novel hybrid multi-robot motion planner that can be applied under non-communication and local observable conditions is presented. The planner is model-free and can realize the end-to-end mapping of multi-robot state and observation information to final smooth and continuous trajectories. The planner is a front-end and back-end separated architecture. The design of the front-end collaborative waypoints searching module is based on the multi-agent soft actor-critic algorithm under the centralized training with decentralized execution diagram. The design of the back-end trajector…
College of Artificial Intelligence, Nankai University（南开大学人工智能学院）；Tianjin Key Laboratory of Intelligent Robotics, Nankai University（南开大学天津智能机器人重点实验室）；School of Marine Science and Technology, Northwestern Polytechnical University（西北工业大学航海学院）；Faculty of Robot Science and Engineering, Northeastern University（东北大学机器人科学与工程学院）；College of Systems Engineering, National University of Defense Technology（国防科技大学系统工程学院）
Local planning is one of the key technologies for mobile robots to achieve full autonomy and has been widely investigated. To evaluate mobile robot local planning approaches in a unified and comprehensive way, a mobile robot local planning benchmark called MRPB 1.0 is newly proposed in this paper. The benchmark facilitates both motion planning researchers who want to compare the performance of a new local planner relative to many other state-of-the-art approaches as well as end users in the mobile robotics industry who want to select a local planner that performs best on some problems of inter…
Multi-mobile robot systems show great advantages over one single robot in many applications. However, the robots are required to form desired task-specified formations, making feasible motions decrease significantly. Thus, it is challenging to determine whether the robots can pass through an obstructed environment under formation constraints, especially in an obstacle-rich environment. Furthermore, is there an optimal path for the robots? To deal with the two problems, a novel graphbased motion planner is proposed in this paper. A mapping between workspace and configuration space of multi-mobi…
This paper extends the gap-based navigation technique in Potential Gap by guaranteeing safety for nonholonomic robots for all tiers of the local planner hierarchy, so called Safer Gap. The first tier generates a Bezier-based collision-free path through gaps. A subset of navigable free-space from the robot through a gap, called the keyhole, is defined to be the union of the largest collision-free disc centered on the robot and a trapezoidal region directed through the gap. It is encoded by a shallow neural network zeroing barrier function (ZBF). Nonlinear model predictive control (NMPC), with K…
Institute of Automation, Chinese Academy of Science（中国科学院自动化研究所）；University of Chinese Academy of Sciences（中国科学院大学）
In the field of navigation and visual servo, it is common to calculate relative pose by feature points on markers, so keeping markers in camera's view is an important problem. In this paper, we propose a novel approach to calculate field-of-view (FOV) constraint of markers for camera. Our method can make the camera maintain the visibility of all feature points during the motion of mobile robot. According to the angular aperture of camera, the mobile robot can obtain the FOV constraint region where the camera cannot keep all feature points in an image. Based on the FOV constraint region, the mo…
University of British Columbia（不列颠哥伦比亚大学）；The Chinese University of Hong Kong（香港中文大学）
Unmanned Aerial Vehicles (UAVs) have been implemented for environmental monitoring by using their capabilities of mobile sensing, autonomous navigation, and remote operation. However, in real-world applications, the limitations of on-board resources (e.g., power supply) of UAVs will constrain the coverage of the monitored area and the number of the acquired samples, which will hinder the performance of field estimation and mapping. Therefore, the issue of constrained resources calls for an efficient sampling planner to schedule UAV-based sensing tasks in environmental monitoring. This paper pr…
Acting and Planning with Hierarchical Operational Models on a Mobile Robot: A Study with RAE+UPOM
German Research Center for Artificial Intelligence (DFKI),Cooperative and Autonomous Systems（德国人工智能研究中心（DFKI））；Osnabrück University（奥斯纳布鲁克大学）；University of Maryland（马里兰大学）；LAAS-CNRS（拉劳斯-CNRS）；Fondazione Bruno Kessler (FBK-ICT)（布鲁诺·克瑟基金会（FBK-ICT））
Dynamic Risk-Aware MPPI for Mobile Robots in Crowds via Efficient Monte Carlo Approximations
Cognitive Robotics Department, TU Delft（代尔夫特理工大学认知机器人部门）；Damen Naval（达门海军）；Centre for Intelligent Transport, Queen Mary University of London（伦敦大学玛丽女王学院智能交通中心）
This paper proposes a process that uses two cameras to obtain three-dimensional (3D) information of a target object for human tracking. Results of human detection and tracking from two cameras are integrated to obtain the 3D information. OpenPose is used for human detection. In the case of a general processing a stereo camera, a range image of the entire scene is acquired as precisely as possible, and then the range image is processed. However, there are problems such as incorrect matching and computational cost for the calibration process. A new stereo vision framework is proposed to cope wit…
University of Southern California（南加利福尼亚大学）；Robert Bosch GmbH（罗伯特·博世股份有限公司）
Planning smooth and energy-efficient motions for wheeled mobile robots is a central task for applications ranging from autonomous driving to service and intralogistic robotics. Over the past decades, a wide variety of motion planners, steer functions and path-improvement techniques have been proposed for such non-holonomic systems. With the objective of comparing this large assortment of state-of-the-art motion-planning techniques, we introduce a novel open-source motion-planning benchmark for wheeled mobile robots, whose scenarios resemble real-world applications (such as navigating warehouse…
We present an approach for estimating a mobile robot's pose w.r.t. the allocentric coordinates of a network of static cameras using multi-view RGB images. The images are processed online, locally on smart edge sensors by deep neural networks to detect the robot and estimate 2D keypoints defined at distinctive positions of the 3D robot model. Robot keypoint detections are synchronized and fused on a central backend, where the robot's pose is estimated via multi-view minimization of reprojection errors. Through the pose estimation from external cameras, the robot's localization can be initialize…
This paper presents PANTHER, a real-time perception-aware (PA) trajectory planner for multirotor-UAVs (Unmanned Aerial Vehicles) in dynamic environments. PANTHER plans trajectories that avoid dynamic obstacles while also keeping them in the sensor field of view (FOV) and minimizing the blur to aid in object tracking. The rotation and translation of the UAV are jointly optimized, which allows PANTHER to fully exploit the differential flatness of multirotors to maximize the PA objective. Real-time performance is achieved by implicitly imposing the underactuated dynamics of the UAV through the Ho…
Hong Kong Polytechnic University（香港理工大学）；The University of Hong Kong（香港大学）
For accomplishing a variety of missions in challenging environments, the capability of navigating with full autonomy while avoiding unexpected obstacles is the most crucial requirement for UAVs in real applications. In this paper, we proposed such a computationally efficient obstacle avoidance trajectory planner that can be used in cluttered unknown environments. Because of the narrow view field of single depth camera on a UAV, the information of obstacles around is quite limited thus the shortest entire path is difficult to achieve. Therefore we focus on the time cost of the trajectory planne…
Data-driven Spatial Classification using Multi-Arm Bandits for Monitoring with Energy-Constrained Mobile Robots
Aerospace Engineering and Mechanics department, University of Minnesota（明尼苏达大学航空航天工程与力学系）；Aeronautics and Astronautics department, Massachusetts Institute of Technology（麻省理工学院航空与航天系）；Mitsubishi Electric Research Laboratories (MERL)（三菱电机研究实验室）
Norwegian University of Life Sciences（挪威生命科学大学）；University of Lincoln（林肯大学）
This paper introduces a new method for robot motion planning and navigation in uneven environments through a surfel representation of underlying point clouds. The proposed method addresses the shortcomings of state-of-the-art navigation methods by incorporating both kinematic and physical constraints of a robot with standard motion planning algorithms (e.g., those from the Open Motion Planning Library), thus enabling efficient sampling-based planners for challenging uneven terrain navigation on raw point cloud maps. Unlike techniques based on Digital Elevation Maps (DEMs), our novel surfel-bas…
In this paper, we provide details of implementing a system for managing a fleet of autonomous mobile robots (AMR) operating in a factory or a warehouse premise. While the robots are themselves autonomous in its motion and obstacle avoidance capability, the target destination for each robot is provided by a global planner. The global planner and the ground vehicles (robots) constitute a multi agent system (MAS) which communicate with each other over a wireless network. Three different approaches are explored for implementation. The first two approaches make use of the distributed computing base…
In this study Arduino card based mobile robot design was realized. This robot can serve as a security robot, an auxiliary robot or a control robot. The designed robot has two operation modes. The first operating mode is autonomous mode. In this mode, the robot detects the surroundings with the help of ultrasonic sensors placed around it, and keeps track of the places it passes by using the encoder. It is able to navigate without hitting any place and passing from where it passes, and it transmits the patient's pulse and temperature condition to the user by other systems installed on it. Also t…
To be useful in everyday environments, robots must be able to identify and locate real-world objects. In recent years, video object segmentation has made significant progress on densely separating such objects from background in real and challenging videos. Building off of this progress, this paper addresses the problem of identifying generic objects and locating them in 3D using a mobile robot with an RGB camera. We achieve this by, first, introducing a video object segmentation-based approach to visual servo control and active perception and, second, developing a new Hadamard-Broyden update …
Depth cameras, typically in RGB-D configurations, are common devices in mobile robotic platforms given their appealing features: high frequency and resolution, low price and power requirements, among others. These sensors may come with significant, non-linear errors in the depth measurements that jeopardize robot tasks, like free-space detection, environment reconstruction or visual robot-human interaction. This paper presents a method to calibrate such systematic errors with the help of a second, more precise range sensor, in our case a radial laser scanner. In contrast to what it may seem at…
Ground Technology Research Institute, Agency for Defense Development（国防发展局地面技术研究所）；DGIST（大邱庆北科学技术院）
Currently, mobile robots are developing rapidly and are finding numerous applications in the industry. However, several problems remain related to their practical use, such as the need for expensive hardware and high power consumption levels. In this study, we build a low-cost indoor mobile robot platform that does not include a LiDAR or a GPU. Then, we design an autonomous navigation architecture that guarantees real-time performance on our platform with an RGB-D camera and a low-end off-the-shelf single board computer. The overall system includes SLAM, global path planning, ground segmentati…
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；University of Chinese Academy of Sciences（中国科学院大学）
Human following on mobile robots has witnessed significant advances due to its potentials for real-world applications. Currently most human following systems are equipped with depth sensors to obtain distance information between human and robot, which suffer from the perception requirements and noises. In this paper, we design a wheeled mobile robot system with monocular pan-tilt camera to follow human, which can stay the target in the field of view and keep following simultaneously. The system consists of fast human detector, real-time and accurate visual tracker, and unified controller for m…
Center for Research on Complex Automated Systems (CASY)（复杂自动化系统研究中心（CASY））；Department of Electrical, Electronic and Information Engineering (DEI)（电气、电子与信息工程系（DEI））；University of Bologna（博洛尼亚大学）
Autonomous exploration is an essential capability for mobile robots, as the majority of their applications require the ability to efficiently collect information about their surroundings. In the literature, there are several approaches, ranging from frontier-based methods to hybrid solutions involving the ability to plan both local and global exploring paths, but only few of them focus on improving local exploration by properly tuning the planned trajectory, often leading to "stop-and-go" like behaviors. In this work we propose a novel RRT-inspired Bézier-based next-best-view trajectory planne…
Stanford University（斯坦福大学）；Nvidia（英伟达公司）；Robotics at Google（谷歌机器人部门）
Many Reinforcement Learning (RL) approaches use joint control signals (positions, velocities, torques) as action space for continuous control tasks. We propose to lift the action space to a higher level in the form of subgoals for a motion generator (a combination of motion planner and trajectory executor). We argue that, by lifting the action space and by leveraging sampling-based motion planners, we can efficiently use RL to solve complex, long-horizon tasks that could not be solved with existing RL methods in the original action space. We propose ReLMoGen -- a framework that combines a lear…
This paper presents Deep-PANTHER, a learning-based perception-aware trajectory planner for unmanned aerial vehicles (UAVs) in dynamic environments. Given the current state of the UAV, and the predicted trajectory and size of the obstacle, Deep-PANTHER generates multiple trajectories to avoid a dynamic obstacle while simultaneously maximizing its presence in the field of view (FOV) of the onboard camera. To obtain a computationally tractable real-time solution, imitation learning is leveraged to train a Deep-PANTHER policy using demonstrations provided by a multimodal optimization-based expert.…
The University of Hong Kong（香港大学）；Baidu Research（百度研究院）
In this paper, we introduce a generalized continuous collision detection (CCD) framework for the mobile robot along the polynomial trajectory in cluttered environments including various static obstacle models. Specifically, we find that the collision conditions between robots and obstacles could be transformed into a set of polynomial inequalities, whose roots can be efficiently solved by the proposed solver. In addition, we test different types of mobile robots with various kinematic and dynamic constraints in our generalized CCD framework and validate that it allows the provable collision ch…
Institute for Digital Technologies, Loughborough University（拉夫堡大学数字技术研究所）
Autonomous robots that assist humans in day to day living tasks are becoming increasingly popular. Autonomous mobile robots operate by sensing and perceiving their surrounding environment to make accurate driving decisions. A combination of several different sensors such as LiDAR, radar, ultrasound sensors and cameras are utilized to sense the surrounding environment of autonomous vehicles. These heterogeneous sensors simultaneously capture various physical attributes of the environment. Such multimodality and redundancy of sensing need to be positively utilized for reliable and consistent per…
Institute for Systems and Robotics, Instituto Superior Técnico, Universidade de Lisboa（里斯本大学高等技术学院系统与机器人研究所）
In this article we purpose a novel method for planar pose estimation of mobile robots. This method is based on an analytic solution (which we derived) for the projection of 3D straight lines, onto the mirror of Non-Central Catadioptric Cameras (NCCS). The resulting solution is rewritten as a function of the rotation and translation parameters, which is then used as an error function for a set of mirror points. Those should be the result of the projection of a set of points incident with the respective 3D lines. The camera's pose is given by minimizing the error function, with the associated co…
University Libre du Bruxelles（布鲁塞尔自由大学）；TU Delft（代尔夫特理工大学）
There is a growing demand for mobile robots to operate in more variable environments, where guaranteeing safe robot navigation is a priority, in addition to time performance. To achieve this, current solutions for local planning use a specific configuration tuned to the characteristics of the application environment. In this paper, we present an approach for developing quality models that can be used by a self-adaptation framework to adapt the local planner configuration at run-time based on the perceived environment. We contribute a definition of a safety model that predicts the safety of a n…
Chalmers University of Technology（查尔姆斯理工大学）；University College London（伦敦大学学院）
There are various trajectory planners for mobile manipulators. It is often challenging to compare their performance under similar circumstances due to differences in hardware, dissimilarity of tasks and objectives, as well as uncertainties in measurements and operating environments. In this paper, we propose a simulation framework to evaluate the performance of the local trajectory planners to generate smooth, and dynamically and kinematically feasible trajectories for mobile manipulators in the same environment. We focus on local planners as they are key components that provide smooth traject…
Motion planning is critical to realize the autonomous operation of mobile robots. As the complexity and randomness of robot application scenarios increase, the planning capability of the classical hierarchical motion planners is challenged. With the development of machine learning, deep reinforcement learning (DRL)-based motion planner has gradually become a research hotspot due to its several advantageous features. DRL-based motion planner is model-free and does not rely on the prior structured map. Most importantly, DRL-based motion planner achieves the unification of the global planner and …
Robotic systems performing end-user oriented autonomous exploration can be deployed in different scenarios which not only require mapping but also simultaneous inspection of regions of interest for the end-user. In this work, we propose a novel Next-Best-View (NBV) planner which can perform full exploration and user-oriented exploration with inspection of the regions of interest using a mobile manipulator robot. We address the exploration-inspection problem as an instance of Multi-Objective Optimization (MOO) and propose a weighted-sum-based information gain function for computing NBVs for the…
Traditional visual navigation methods of micro aerial vehicle (MAV) usually calculate a passable path that satisfies the constraints depending on a prior map. However, these methods have issues such as high demand for computing resources and poor robustness in face of unfamiliar environments. Aiming to solve the above problems, we propose a neuromorphic reinforcement learning method (Neuro-Planner) that combines spiking neural network (SNN) and deep reinforcement learning (DRL) to realize MAV 3D visual navigation with depth camera. Specifically, we design spiking actor network based on two-sta…
Woven Planet United Kingdom Limited（Woven Planet英国有限公司）
With the Autonomous Vehicle (AV) industry shifting towards machine-learned approaches for motion planning, the performance of self-driving systems is starting to rely heavily on large quantities of expert driving demonstrations. However, collecting this demonstration data typically involves expensive HD sensor suites (LiDAR + RADAR + cameras), which quickly becomes financially infeasible at the scales required. This motivates the use of commodity sensors like cameras for data collection, which are an order of magnitude cheaper than HD sensor suites, but offer lower fidelity. Leveraging these s…
Norwegian University of Life Sciences（挪威生命科学大学）；University of Lincoln（林肯大学）
Sampling-Based Optimal(SBO) path planning has been mainly used for robotic arm manipulation tasks. Several research works have been carried out in order to evaluate performances of various SBO planners for arm manipulation. However, not much of work is available that highlights performances of SBO planners in context of mobile robot navigation in outdoor 3D environments. This paper evaluates performances of major SBO planners in Open Motion Planning Library(OMPL) for that purpose. Due to large number of existing SBO planners, experimenting and selecting a proper planner for a planning problem …
Open-Source, Cost-Aware Kinematically Feasible Planning for Mobile and Surface Robotics
Open Navigation LLC；Carnegie Mellon University（卡内基梅隆大学）；Locus Robotics；QUT Centre for Robotics and School of Electrical Engineering and Robotics（QUT机器人中心和电气工程与机器人学院）
