Autonomous object search is challenging for mobile robots operating in indoor environments due to partial observability, perceptual uncertainty, and the need to trade off exploration and navigation efficiency. Classical probabilistic approaches explicitly represent uncertainty but typically rely on handcrafted action-selection heuristics, while deep reinforcement learning enables adaptive policies but often suffers from slow convergence and limited interpretability. This paper proposes a hybrid object-search framework that integrates Bayesian inference with deep reinforcement learning. The method maintains a spatial belief map over target locations, updated online through Bayesian inference from calibrated object detections, and trains a reinforcement learning policy to select navigation actions directly from this probabilistic representation. The approach is evaluated in realistic indoor simulation using Habitat 3.0 and compared against developed baseline strategies. Across two indoor environments, the proposed method improves success rate while reducing search effort. Overall, the results support the value of combining Bayesian belief estimation with learned action selection to achieve more efficient and reliable objectsearch behavior under partial observability.
With the rise of automation, unmanned vehicles became a hot topic both as commercial products and as a scientific research topic. It composes a multi-disciplinary field of robotics that encompasses embedded systems, control theory, path planning, Simultaneous Localization and Mapping (SLAM), scene reconstruction, and pattern recognition. In this work, we present our exploratory research of how sensor data fusion and state-of-the-art machine learning algorithms can perform the Embodied Artificial Intelligence (E-AI) task called Visual Semantic Navigation. This task, a.k.a Object-Goal Navigation…
What Matters in RL-Based Methods for Object-Goal Navigation? An Empirical Study and A Unified Framework
Computer Vision and Geometry Group, ETH Zurich, Switzerland（苏黎世联邦理工学院计算机视觉与几何组）；Robotics and Perception Group, University of Zurich, Switzerland（苏黎世大学机器人与感知组）；Robotic Systems Lab, ETH Zurich, Switzerland（苏黎世联邦理工学院机器人系统实验室）；Princeton Robotic Intelligence and SysteMs group, Princeton University, USA（普林斯顿大学机器人智能与系统组）；Microsoft, Switzerland（微软公司）
Advancements in deep learning over the years have attracted research into how deep artificial neural networks can be used in robotic systems. This research survey will present a summarization of the current research with a specific focus on the gains and obstacles for deep learning to be applied to mobile robotics.
Bristol Research and Innovation Laboratory, Toshiba Europe Ltd.（东芝欧洲有限公司布里斯托尔研究与创新实验室）
Mobile robots have disrupted the material handling industry which is witnessing radical changes. The requirement for enhanced automation across various industry segments often entails mobile robotic systems operating in logistics facilities with little/no infrastructure. In such environments, out-of-box low-cost robotic solutions are desirable. Wireless connectivity plays a crucial role in successful operation of such mobile robotic systems. A wireless mesh network of mobile robots is an attractive solution; however, a number of system-level challenges create unique and stringent service requi…
We were able to complete the full integration of the Robotic Technology Kernel (RTK) into an electric vehicle by-wire system using lidar and GPS sensors. The solution included a mobile application to interface with the RTK-enabled autonomous vehicle. Altogether the system was designed to be modular, using the concepts of message-based software design that is built into the Robot Operating System (ROS), which is at the foundation of RTK. The team worked incrementally to develop working software to demonstrate each milestone on the path to successfully completing the RTK integration for the deve…
In the past ten years, the use of 3D Time-of-Flight (ToF) LiDARs in mobile robotics has grown rapidly. Based on our accumulation of relevant research, this article systematically reviews and analyzes the use 3D ToF LiDARs in research and industrial applications. The former includes object detection, robot localization, long-term autonomy, LiDAR data processing under adverse weather conditions, and sensor fusion. The latter encompasses service robots, assisted and autonomous driving, and recent applications performed in response to public health crises. We hope that our efforts can effectively …
Efficient routing is one of the key challenges of wireless networking for unmanned autonomous vehicles (UAVs) due to dynamically changing channel and network topology characteristics. Various well known mobile-ad-hoc routing protocols, such as AODV, OLSR and B.A.T.M.A.N. have been proposed to allow for proactive and reactive routing decisions. In this paper, we present a novel approach which leverages application layer knowledge derived from mobility control algorithms guiding the behavior of UAVs to fulfill a dedicated task. Thereby a prediction of future trajectories of the UAVs can be integ…
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…
This paper presents the concept of an In situ Fabricator, a mobile robot intended for on-site manufacturing, assembly and digital fabrication. We present an overview of a prototype system, its capabilities, and highlight the importance of high-performance control, estimation and planning algorithms for achieving desired construction goals. Next, we detail on two architectural application scenarios: first, building a full-size undulating brick wall, which required a number of repositioning and autonomous localisation manoeuvres. Second, the Mesh Mould concrete process, which shows that an In si…
Inovasyon Muhendislik Ltd. Sti.（创新工程有限公司）；Research and Development Department（研发部门）
The use of mobile robots has inevitably increased in recent years. The increase in the companies that produce products in this field, the popularity of the studies in the robotic field and the technological competence to serve many different areas have revealed this increase in usage. The importance of mobile robots used as health, education, pro-duction, logistics, defense industry and space equipment is now more important than before. The fact that robotic education can be reduced to a very young age, the production and coding of simple robots with easily accessible parts is also an importan…
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…
GRASP Lab at Ontario Tech University（安大略理工大学GRASP实验室）
This paper presents the application of the concepts and approaches of linear graph (LG) theory in the modeling and simulation of a 4-wheel skid-steer mobile robotic system. An LG representation of the system is proposed and the accompanying state-space model of the dynamics of a mobile robot system is evaluated using the associated LGtheory MATLAB toolbox, which was developed in our lab. A genetic algorithm (GA)-based parameter estimation method is employed to determine the system parameters, which leads to a very accurate simulation of the model. The developed model is then evaluated and vali…
Evaluation of Three Vision Based Object Perception Methods for a Mobile Robot
Artificial Intelligence Research Institute (IIIA-CSIC)（人工智能研究所 (IIIA-CSIC)）；Computer Vision Center（计算机视觉中心）；Australian Centre for Field Robotics（澳大利亚野外机器人中心）；The University of Sydney（悉尼大学）
Koopman operator theory has served as the basis to extract dynamics for nonlinear system modeling and control across settings, including non-holonomic mobile robot control. There is a growing interest in research to derive robustness (and/or safety) guarantees for systems the dynamics of which are extracted via the Koopman operator. In this paper, we propose a way to quantify the prediction error because of noisy measurements when the Koopman operator is approximated via Extended Dynamic Mode Decomposition. We further develop an enhanced robot control strategy to endow robustness to a class of…
Robotics simulation provides many advantages during the development of an intelligent ground vehicle (IGV) such as testing the software components in varying scenarios without requiring a complete physical robot. This paper discusses a 3D simulation environment created using rapid application development and the Unity game engine to enable testing during a mobile robotics competition. Our experience shows that the simulation environment contributed greatly to the development of software for the competition. The simulator also contributed to the hardware development of the robot.
Navigation in an unknown environment without any preexisting positioning infrastructure has always been hard for mobile robots. This paper presents a self-deployable ultra wideband UWB infrastructure by mobile agents, that permits a dynamic placement and runtime extension of UWB anchors infrastructure while the robot explores the new environment. We provide a detailed analysis of the uncertainty of the positioning system while the UWB infrastructure grows. Moreover, we developed a genetic algorithm that minimizes the deployment of new anchors, saving energy and resources on the mobile robot an…
Inspired by a couple of simple organisms without eyes, neither ears. This paper presents a novel hybrid bionic robot, called "particle robot", which mix a macro-organism and a micro-organism in the same robot. On one hand, an interesting rather boring animal, the biological Echinoids (sea urchins) is mixed with the viruses micro-organisms, in specific the rotaviruses; together with spherical mobile robots. Analogously, from a pure robotic perspective, this bio-inspired robot can be seen as a spherical mobile robot wearing an actuated exoskeleton. The robot has two main configurations: when the…
THUD++: Large-Scale Dynamic Indoor Scene Dataset and Benchmark for Mobile Robots
Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；Department of Computer Science and Technology, Tsinghua University（清华大学计算机科学与技术系）
PREVENT: Proactive Risk Evaluation and Vigilant Execution of Tasks for Mobile Robotic Chemists using Multi-Modal Behavior Trees
Department of Chemistry and Material Innovation Factory, University of Liverpool（化学系和材料创新工厂，利物浦大学）；Center for Life Science Automation, University of Rostock（生命科学自动化中心，罗斯托克大学）
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The Pennsylvania State University（宾夕法尼亚州立大学）；Penn State Harrisburg（宾州州立大学哈里斯堡分校）
This paper investigates deception in the context of motion using a simulated mobile robot. We analyze some previously designed deceptive strategies on a mobile robot simulator. We then present a novel approach to adaptively choose target-oriented deceptive trajectories to deceive humans for multiple interactions. Additionally, we propose a new metric to evaluate deception on data collected from the users when interacting with the mobile robot simulator. We performed a user study to test our proposed adaptive deceptive algorithm, which shows that our algorithm deceives humans even for multiple …
The implementation of robots to enhance some processes has become popular in recent years due to the accelerated way of production in some factories. Within this context was where robotics has emerged, firstly with stationary robots and more recently mobile robots, namely aerial and terrestrial robots. They can be used for delimited processes within a function, mainly the stationary robots, but also for research in wider areas and even competition. This work summarizes the construction of a model of terrestrial mobile robot that makes the use of artificial intelligence for the purpose of resea…
This paper proposes a framework to measure the important metrics (throughput, delay, packet retransmits, signal strength, etc.) to determine Wi-Fi network performance of mobile robots supported by the Robot Operating Systems (ROS) middleware. We analyze the bidirectional network performance of mobile robots through an experimental setup in an indoor environment, where a mobile robot is communicating vital sensor data such as video streaming from the camera(s) and LiDAR scan values to a command station while it navigates an indoor environment through teleoperated velocity commands received from…
Coordinated Science Laboratory（协同科学实验室）；University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）
The StarL programming framework aims to simplify development of distributed robotic applications by providing easy-to-use language constructs for communication and control. It has been used to develop applications such as formation control, distributed tracking, and collaborative search. In this paper, we present a complete redesign of the StarL language and its runtime system which enables us to achieve portability of robot programs across platforms. Thus, the same application program, say, for distributed tracking, can now be compiled and deployed on multiple, heterogeneous robotic platforms…
Socially-aware Object Transportation by a Mobile Manipulator in Static Planar Environments with Obstacles
Computer Vision and Robotics Laboratory (VeRLab), Department of Computer Science, Universidade Federal de Minas Gerais（计算机视觉与机器人实验室（VeRLab）、计算机科学系、巴西矿务大学）
This paper aims to implement Object-Oriented Markov Decision Process (OO-MDPs) for goal planning and navigation of robot in an indoor environment. We use the OO-MDP representation of the environment which is a natural way of modeling the environment based on objects and their interactions. The paper aims to extend the well known Taxi domain example which has been tested on grid world environment to robotics domain with larger state-spaces. For the purpose of this project we have created simulation of the environment and robot in ROS with Gazebo and Rviz as visualization tools.The mobile robot …
We propose a physics-based method to learn environmental fields (EFs) using a mobile robot. Common purely data-driven methods require prohibitively many measurements to accurately learn such complex EFs. Alternatively, physics-based models provide global knowledge of EFs but require experimental validation, depend on uncertain parameters, and are intractable for mobile robots. To address these challenges, we propose a Bayesian framework to select the most likely physics-based models of EFs in real-time, from a pool of numerical solutions generated offline as a function of the uncertain paramet…
Team Mountaineers launched efforts on the NASA Space Robotics Challenge Phase-2 (SRC2). The challenge will be held on the lunar terrain with virtual robotic platforms to establish an in-situ resource utilization process. In this report, we provide an overview of a simulation environment, a virtual mobile robot, and a software architecture that was created by Team Mountaineers in order to prepare for the competition's qualification round before the competition environment was released.
In this paper, we propose a framework for the control of mobile robots subject to temporal logic specifications using barrier functions. Complex task specifications can be conveniently encoded using linear temporal logic. In particular, we consider a fragment of linear temporal logic which encompasses a large class of motion planning specifications for a robotic system. Control barrier functions have recently emerged as a convenient tool to guarantee reachability and safety for a system. In addition, they can be encoded as affine constraints in a quadratic program. In this paper, a fully autom…
TECNALIA, Basque Research and Technology Alliance (BRTA)（TECNALIA，巴斯克研究与技术联盟）；University of the Basque Country (UPV-EHU)（巴斯克国家大学）；Robotics and Autonomous Systems Group (RSAIT)（机器人与自主系统组）
The thrust for increased rating capacity of wind turbines has resulted into larger generators, longer blades, and taller towers. Presently, up to 16 MW wind turbines are being offered by wind turbines manufacturers which is nearly a 60 percent increase in the design capacity over the last five years. Manufacturing of these turbines involves assembling of gigantic sized components. Due to the frequent design changes and the variety of tasks involved, conventional automation is not possible making it a labor-intensive activity. However the handling and assembling of large components are challeng…
Vision Language Model-based Testing of Industrial Autonomous Mobile Robots
Simula Research Laboratory and University of Oslo（Simula研究实验室和奥斯陆大学）；Mondragon University（蒙dragon大学）；Simula Research Laboratory（Simula研究实验室）；PAL Robotics（PAL机器人技术）
Uncertainty-Informed Active Perception for Open Vocabulary Object Goal Navigation
Center for Robotics, University of Bonn（波恩大学机器人中心）；MAVLab, TU Delft（代尔夫特理工大学MAVLab）；Lamarr Institute for Machine Learning and Artificial Intelligence（机器学习与人工智能拉马尔研究所）
We present four different robust transfer learning and data augmentation strategies for robust mobile scene recognition. By training three mobile-ready (EfficientNetB0, MobileNetV2, MobileNetV3) and two large-scale baseline (VGG16, ResNet50) convolutional neural network architectures on the widely available Event8, Scene15, Stanford40, and MIT67 datasets, we show the generalization ability of our transfer learning strategies. Furthermore, we tested the robustness of our transfer learning strategies under viewpoint and lighting changes using the KTH-Idol2 database. Also, the impact of inference…
University of Paderborn（帕德博恩大学）；Leuphana University of Lüneburg（吕讷堡莱法纳大学）
This paper presents a collection of path planning algorithms for real-time movement of multiple robots across a Robotic Mobile Fulfillment System (RMFS). Robots are assigned to move storage units to pickers at working stations instead of requiring pickers to go to the storage area. Path planning algorithms aim to find paths for the robots to fulfill the requests without collisions or deadlocks. The state-of-the-art path planning algorithms, including WHCA*, FAR, BCP, OD&ID and CBS, were adapted to suit path planning in RMFS and integrated within a simulation tool to guide the robots from their…
