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This paper proposes a reliable and straightforward approach to mobile robots (or moving objects in general) indoor tracking, in order to perform a preliminary study on their dynamics. The main features of this approach are its minimal and low-cost setup and a user-friendly interpretation of the data generated by the ArUco library. By using a common...
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Automated object detection systems are a key component of modern surveillance applications. These systems rely on computationally expensive computer vision algorithms that perform object detection on visual data recorded by surveillance cameras. Due to the security and safety implications of these systems, this visual data must be processed accurat...
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... The upper camera is a static USB RGB (red, green, blue) camera connected to an embedded computer (e.g., Raspberry Pi 3B+), pointing towards the workspace; all the markers are ArUco Fiducial Markers [14], with reference markers fixed to the road and mobile markers fixed to each car. The work [15] has a detailed explanation of how the ArUco library works and how it can be implemented for mobile robot tracking. ...
In this work, DonkieTown is introduced, an affordable and scalable platform for research on autonomous vehicles. The experimental framework was developed in the Robot Operative System (ROS). The platform integrates multiple small scale autonomous vehicles called Asinus Cars, which are equipped with at least a camera, odometer, and onboard computer. The vehicles are Differential Drive Robots (DDR), forced by software to behave as car-like vehicles. DonkieTown incorporates a low-cost localization system to provide the real-time vehicles' pose, by means of external cameras which detect ArUco markers, then Kalman Filters (KF) are used to track and estimate the pose of each vehicle. The platform includes a base station computer with a graphical interface for monitoring the system. DonkieTown also includes a series of algorithms to facilitate autonomous driving, such as communication, tracking, object detection, obstacle avoidance, control, trajectory tracking, etc. Moreover, a centralized vehicular network is implemented to allow communication between the agents and the base station, where the agents can share information about their state, obstacles, maneuver intentions, etc. To facilitate the research on autonomous cars in Latin America, the developed libraries are released as open source. Real-time experiments demonstrate the performance of DonkieTown in autonomous driving missions, such as following a lane while avoiding Donkey-like obstacles, and collaborative autonomous driving in convoy.
... Moreover, collision detection and avoidance can be interesting ideas. Similarly, Botta and Quaglia [112] used ArUco markers [140] for mobile robots. However, their system can be used for general indoor navigation. ...
Indoor navigation has remained an active research area for the last decade. Unlike outdoor environments, indoor environments have additional challenges, such as weak signals, low light, and complex scenarios. Different technologies are used for indoor navigation, including WiFi, Bluetooth, inertial sensors, and computer cameras. Vision-based methods have great potentials for indoor navigation as they fulfill most of the general requirements such as minimal cost, ease of use, ease of implementation, and realism. Therefore, researchers have successively proposed different novel vision-based approaches for indoor navigation. Unfortunately, there is no standard review article (except a few general reviews) that covers the current trends and draws a pipeline for future research. In this paper, we reviewed the current state-of-the-art vision-based indoor navigation methods. We followed the systematic literature review (SLR) methodology for article searching, selection, and quality assessments. In total, we selected 68 articles after final selection using SLR. We classified these articles into different categories. Each article is briefly studied for information extraction, including key idea, category of the article, evaluation criterion, and its strengths and weaknesses. We also highlighted several interesting future directions. This study will help new researchers to grasp the research challenge as well as present the results of their research in the field. It will also help the community to find a suitable indoor navigation system according to users’ requirements.
... Our proposal refers to an AI-enabled tool for generating representative tracking points to capture the position of different products and close the control loop of CAM systems. Instead of relying on fiducial [24] or other markers that affect an object's appearance, our conceptualization refers to the application of highly infrared (IR) reflective materials, such as Aluminum or Magnesium Oxide, to strategically selected by the AI [25] regions of each product. Such materials can be easily perceived by an IR camera sensor without significantly interfering with the final form of the product, facilitating the tracking and handling procedures of a modern production line with multiple robotic manipulators. ...
The paper at hand presents a novel and versatile method for tracking the pose of varying products during their manufacturing procedure. By using modern Deep Neural Network techniques based on Attention models, the most representative points to track an object can be automatically identified using its drawing. Then, during manufacturing, the body of the product is processed with Aluminum Oxide on those points, which is unobtrusive in the visible spectrum, but easily distinguishable from infrared cameras. Our proposal allows for the inclusion of Artificial Intelligence in Computer-Aided Manufacturing to assist the autonomous control of robotic handlers.
... Relevant on-board measurements, such as motor angular speed, were transmitted in real-time to a PC, where they were logged. The visual-based tracking system, described in depth in [23] and summarised in the following section, was used to track the actual trajectory of the robot. Several tests at different motor speeds were performed and then used to compare the actual trajectory with the theoretical one. ...
In this paper, the effects of wheel slip compensation in trajectory planning for mobile tractor-trailer robot applications are investigated. Firstly, a kinematic model of the proposed robot architecture is marked out, then an experimental campaign is done to identify if it is possible to kinematically compensate trajectories that otherwise would be subject to large lateral slip. Due to the close connection to the experimental data, the results shown are valid only for Epi.q, the prototype that is the main object of this manuscript. Nonetheless, the base concept can be usefully applied to any mobile robot subject to large lateral slip.
... In order to overcome the problem of estimating the position and yaw angle, computer vision has been included in the procedure. Despite the high computational cost required, several studies applied visual techniques to obtain system state estimation (Lee et al. (2012), Li et al. (2017), Santos and Gonçalves (2017), Botta and Quaglia (2020)) since its information is more reliable compared to MEMS sensors. As the computational power of the lowcost embedded system grows up in the last years, computer vision has become a feasible alternative when the inclusion of GPS and magnetometer are not available or have low reliability. ...
... Moreover, collision detection and avoidance can be interesting ideas. Similarly, Botta and Quaglia [112] used ArUco markers [140] for mobile robots. However, their system can be used for general indoor navigation. ...
Marker-based systems are one of the good tracking approaches used for augmented reality applications. Their registration is very accurate and no delay is noticeable, when overlying the virtual information on a real-world scene. However, markers often suffer from a limited tracking range entailing rare use in long range augmented reality applications. This paper presents a method for the automatic generation of a layered marker, a marker that can be tracked from short as well as long distances. An evaluation of a layered marker was performed employing the standard ARToolKit framework. The analysis shows that an automatic created layered marker extends the tracking range. The same marker can be successfully tracked from small and long distances; thus can be used in the development of such augmented reality applications that need long tracking range.
In recent years, autonomous vehicles and mobile robots are starting to become a trend also in several new fields of application. In some cases, they are articulated vehicles with an active front module and a rear one that is pulled passively or that can contribute to the vehicle traction when required. Although modelling of mobile robots is not a novelty, most of the available studies are limited to kinematic or very basic dynamic models. In order to correctly simulate mobile robots with fast dynamics or operating off-road, this study proposes a dynamic model of such systems derived taking into account lateral and longitudinal slip in the wheels. The model is then validated experimentally using a small articulated robot.
