Browsing by Author "Alajlan, Maram"
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- Design and performance analysis of global path planning techniques for autonomous mobile robots in grid environmentsPublication . Chaari, Imen; Koubâa, Anis; Bennaceur, Hachemi; Ammar, Adel; Alajlan, Maram; Youssef, HabibThis article presents the results of the 2-year iroboapp research project that aims at devising path planning algorithms for large grid maps with much faster execution times while tolerating very small slacks with respect to the optimal path. We investigated both exact and heuristic methods. We contributed with the design, analysis, evaluation, implementation and experimentation of several algorithms for grid map path planning for both exact and heuristic methods. We also designed an innovative algorithm called relaxed A-star that has linear complexity with relaxed constraints, which provides near-optimal solutions with an extremely reduced execution time as compared to A-star. We evaluated the performance of the different algorithms and concluded that relaxed A-star is the best path planner as it provides a good trade-off among all the metrics, but we noticed that heuristic methods have good features that can be exploited to improve the solution of the relaxed exact method. This led us to design new hybrid algorithms that combine our relaxed A-star with heuristic methods which improve the solution quality of relaxed A-star at the cost of slightly higher execution time, while remaining much faster than A* for large-scale problems. Finally, we demonstrate how to integrate the relaxed A-star algorithm in the robot operating system as a global path planner and show that it outperforms its default path planner with an execution time 38% faster on average.
- Dronemap Planner: A Service-Oriented Cloud-Based Management System for the Internet-of-DronesPublication . Koubaa, Anis; Qureshi, Basit; Sriti, Mohamed-Foued; Allouch, Azza; Javed, Yasir; Alajlan, Maram; Cheikhrouhou, Omar; Khalgui, Mohamed; Tovar, EduardoLow-cost Unmanned Aerial Vehicles (UAVs), also known as drones, are increasingly gaining interest for enabling novel commercial and civil Internet-of-Things (IoT) applications. However, there are still open challenges that restrain their real-world deployment. First, drones typically have limited wireless communication ranges with the ground stations preventing their control over large distances. Second, these low-cost aerial platforms have limited computation and energy resources preventing them from running heavy applications onboard. In this paper, we address this gap and we present Dronemap Planner (DP), a service-oriented cloud-based drone management system that controls, monitors and communicates with drones over the Internet. DP allows seamless communication with the drones over the Internet, which enables their control anywhere and anytime without restriction on distance. In addition, DP provides access to cloud computing resources for drones to offload heavy computations. It virtualizes the access to drones through Web services (SOAP and REST), schedules their missions, and promotes collaboration between drones. DP supports two communication protocols: (i.) the MAVLink protocol, which is a lightweight message marshaling protocol supported by commodities Ardupilot-based drones. (ii.) the ROSLink protocol, which is a communication protocol that we developed to integrate Robot Operating System (ROS)-enabled robots into the IoT. We present several applications and proof-of-concepts that were developed using DP. We demonstrate the effectiveness of DP through a performance evaluation study using a real drone for a real-time tracking application.
- Global robot Path Planning using GA for Large Grid Maps: Modelling, Performance and ExperimentationPublication . Alajlan, Maram; Chaari, Imen; Koubâa, Anis; Bennaceur, Hachemi; Ammar, Adel; Youssef, HabibIn this paper, the efficiency of genetic algorithm (GA) approach to address the problem of global path planning for mobile robots in large-scale grid environments is revisited and assessed. First, an efficient GA path planner to find an (or near) optimal path in a grid map is proposed. In particular, large maps instances are considered in this work, as small maps are easy to address by typical linear-time exact algorithms, in contrast to large maps, which require more intensive computations. The operators of the GA planner were carefully designed for optimizing the search process. Also, extensive simulations to evaluate the GA planner are conducted, and its performance is compared to that of the A algorithm considered as benchmarking reference. We found out that the GA planner can find optimal solutions in the same way as A in large grid maps in most cases, but A is faster than the GA. This is because GA is not a constructive path planner and heavily relies on initial population to explore the space of solutions in contrast to A that builds its solution progressively towards the target. It was concluded that, although GA can provide an alternative to A technique, it is likely that they are not efficient enough to beat exact methods such as A when used with a consistent heuristic. The GA planner is integrated in the global path planning modules of the Robot Operating System (ROS), its feasibility is demonstrated, and its performance is compared against the default ROS planner.
- Micro Air Vehicle Link (MAVLink) in a Nutshell: A SurveyPublication . Koubaa, Anis; Allouch, Azza; Alajlan, Maram; Javed, Yasir; Belghith, Abdelfettah; Khalgui, MohamedThe micro air vehicle link (MAVLink in short) is a communication protocol for unmanned systems (e.g., drones and robots). It specifies a comprehensive set of messages exchanged between unmanned systems and ground stations. This protocol is used in major autopilot systems, mainly ArduPilot and PX4, and provides powerful features not only for monitoring and controlling unmanned systems missions but also for their integration into the Internet. However, there is no technical survey and/or tutorial in the literature that presents these features or explains how to make use of them. Most of the references are online tutorials and basic technical reports, and none of them presents comprehensive and systematic coverage of the protocol. In this paper, we address this gap, and we propose an overview of the MAVLink protocol, the difference between its versions, and it is potential in enabling Internet connectivity to unmanned systems. We also discuss the security aspects of the MAVLink. To the best of our knowledge, this is the first technical survey and tutorial on the MAVLink protocol, which represents an important reference for unmanned systems users and developers.
- MyBot: Cloud-Based Service Robot using Service-Oriented ArchitecturePublication . Koubâa, Anis; Sriti, Mohamed-Foued; Javed, Yasir; Alajlan, Maram; Qureshi, Basit; Ellouze, Fatma; Mahmoud, AbdelrahmanThis paper presents a viable solution for the development of service robots by leveraging cloud and Web services technologies, modular software architecture design, and Robot Operating System (ROS). The contributions of this paper are two- folded (1) Design of ROS Web services to provide new abstract interfaces to service robots that makes easier the interaction with and the development of service robots applications, and (2) Integration of the service robot to the cloud using the ROSLink protocol. We demonstrate through real-world implementation on the MyBot robot the effectiveness of these software abstraction layers in developing applications for service robots through the Internet and the cloud, and in accessing them through Internet. We believe that this work represents an important step towards a more popular use of service robots.
- Performance of a Low Cost Hadoop Cluster for Image Analysis in Cloud Robotics EnvironmentPublication . Qureshi, Basit; Javed, Yasir; Koubâa, Anis; Sriti, Mohamed-Foued; Alajlan, MaramWith the emergence of cloud robotics, the cloud computing paradigm becomes increasingly attractive to robotics, where the cloud acts as the remote brain of low-cost robots, such as commodity drones. The idea is to offload heavy computations, like image processing, from the robot to the cloud; process it in short time (near real-time) and send back commands to the robot. This paper investigates the performance of a back-end cloud computing framework in deploying robotics-like applications (i.e. image analysis and processing) using low-cost Hadoop clusters. The design of a low-cost mini-data center built with readily available commodity 32-bit ARM boards, i.e. Raspberry Pi 2 Model B, is presented. Furthermore, the performance of RPi-based clusters is extensively tested with different types of data including text, text/image and image, and a comparative analysis against Hadoop cluster running on virtual machines is presented. The Hadoop Image Processing Interface (HIPI) Library was used and also configured to optimally utilize the Pi Cluster resources for improved performance. Results show that the RPi Hadoop cluster lags in performance when compared to Hadoop cluster running on virtual machines, the low cost and small form factor makes it ideal for remote Image analysis in surveillance / disaster recovery scenarios where UAVs can transmit image streams to the Cluster for remote processing.
- Relaxed Dijkstra and A* with linear complexity for robot path planning problems in large-scale grid environmentsPublication . Ammar, Adel; Bennaceur, Hachemi; Châari, Imen; Koubâa, Anis; Alajlan, MaramAlthough there exist efficient methods to determine an optimal path in a graph, such as Dijkstra and A* algorithms, large instances of the path planning problem need more adequate and efficient techniques to obtain solutions in reasonable time. We propose two new time-linear relaxed versions of Dijkstra (RD) and A* (RA*) algorithms to solve the global path planning problem in large grid environments. The core idea consists in exploiting the grid-map structure to establish an accurate approximation of the optimal path, without visiting any cell more than once. We conducted extensive simulations (1290 runs on 43 maps of various types) for the proposed algorithms, both in four-neighbor and eight-neighbor grid environments, and compared them against original Dijkstra and A* algorithms with different heuristics. We demonstrate that our relaxed versions exhibit a substantial gain in terms of computational time (more than 3 times faster in average), and in most of tested problems an optimal solution (in at least 97 % of cases for RD and 82 % for RA*) or a very close one is reached (at most 9 % of extra length, and less than 2 % in average). Besides, the simulations also show that RA* provides a better trade-off between solution quality and execution time than previous bounded relaxations of A* that exist in the literature.
- Robot Path Planning and CooperationPublication . Koubaa, Anis; Bennaceur, Hachemi; Chaari, Imen; Trigui, Sahar; Ammar, Adel; Sriti, Mohamed-Foued; Alajlan, Maram; Cheikhrouhou, Omar; Javed, YasirThis book presents extensive research on two main problems in robotics: the path planning problem and the multi-robot task allocation problem. It is the first book to provide a comprehensive solution for using these techniques in large-scale environments containing randomly scattered obstacles. The research conducted resulted in tangible results both in theory and in practice. For path planning, new algorithms for large-scale problems are devised and implemented and integrated into the Robot Operating System (ROS). The book also discusses the parallelism advantage of cloud computing techniques to solve the path planning problem, and, for multi-robot task allocation, it addresses the task assignment problem and the multiple traveling salesman problem for mobile robots applications. In addition, four new algorithms have been devised to investigate the cooperation issues with extensive simulations and comparative performance evaluation. The algorithms are implemented and simulated in MATLAB and Webots.
- Turtlebot at Office: A Service-Oriented Software Architecture for Personal Assistant Robots using ROSPublication . Koubâa, Anis; Sriti, Mohamed-Foued; Javed, Yasir; Alajlan, Maram; Qureshi, Basit; Ellouze, Fatma; Mahmoud, AbdelrahmanThis paper presents the design of an assistive mobile robot to support people in their everyday activities in office and home environments. The contribution of this paper consists in the design of a modular component-based software architecture that provides different abstraction layers on top of Robot Operating System (ROS) to make easier the design and development of service robots with ROS. The first abstraction layer is the COROS framework composed of complementary software subsystems providing different interfaces between ROS and the client applications. The second abstraction layer is the integration of Web services into ROS to allow client applications to seamlessly and transparently interact with the robot while hiding all implementation details. The proposed software architecture was validated through a experimental prototype of Turtlebot deployed in University campus. Furthermore, we outline the challenges incurred during experimentation and focus on lessons learned throughout the implementation and deployment.