A new cloud autonomous system as a service for multi-mobile robots

Neural Computing and Applications https://doi.org/10.1007/s00521-022-07605-7 (0123456789().,-volV)(0123456789(). ,- volV) ORIGINAL ARTICLE A new cloud autonomous system as a service for multi-mobile robots Aida A. Nasr1 Received: 1 December 2021 / Accepted: 1 July 2022  The Author(s) 2022 Abstract Today, mobile robot is used in most industrial and commercial fields. It can improve and carry out work complex tasks quickly and efficiently. However, using swarm robots to execute some tasks requires a complex system for assigning robots to these tasks. The main issue in the robot control systems is the limited facilities of robot embedded system components. Although, some researchers used cloud computing to develop robot services. They didn’t use the cloud for solving robot control issues. In this paper, we have used cloud computing for controlling robots to solve the problem of limited robot processing components. The main advantage of using cloud computing is its intensive computing power. This advantage motivates us to propose a new autonomous system for multi-mobile robots as a services-based cloud computing. The proposed system consists of three phases: clustering phase, allocation phase, and path planning phase. It groups all tasks/duties into clusters using the k-means algorithm. After that, it finds the optimal path for each robot to execute its duties in the cluster based on the Nearest neighbor and Harris Hawks Optimizer (HHO). The proposed system is compared with systems that use a genetic algorithm, simulated annealing algorithm, and HHO algorithm. From the finding, we find that the proposed system is more efficient than the other systems in terms of decision time, throughput, and the total distance of each robot. Keywords Multi-robot  Cloud computing  HHO  Autonomous system  Path planning  Scheduling 1 Introduction Today mobile robot is used in many locations: streets, factories, government organizations, hospitals, and universities. They can move and explore, transport things and goods, and complete complex tasks. Moreover, scientists use mobile robots in space and ocean exploration [1–3]. One example of space exploration is NASA tried sending robots for exploration in regions called analogs (i.e. analog is a location where the environment is hassling to locations like Mars or the moon, where a robot may be used). One NASA analog exists in the Arizona desert. NASA robotics specialists perform experiments in the desert to estimate new ideas for rovers, spacewalks, and ground support. Some of these experiments are performed by a group called & Aida A. Nasr 1 Information Technology Department, Faculty of Computers and Informatics, Tanta University, Tanta, Egypt Desert RATS, which is referred to by Desert Research and Technology Studies [4]. The multi-mobile robot system (MMRS) is a group of robots that are cooperating in performing one task/ duty or performing some tasks/duties related to each other [5]. This kind of robot system needs an efficient plan for executing duties and communicating with each other. To implement the MMRS management system, robot engineers need some powerful robot components to be fast and operate in real-time. Outfitting each robot in a swarm with highpowered components results in a massive and expensive robot. While the use of cloud computing may be an ideal solution to solve this problem, cloud computing is characterized by high-performance capabilities and great speed in performing various data processing resulting in reduced response time. In addition, using cloud computing services is cheaper than building robot components and implementing a system for each robot [6]. Last years, researchers and cloud engineers began to use cloud computing for developing robotic systems as a service. Researchers in [7, 8] showed the idea of using cloud computing with robotic systems for executing tasks. The 123 Neural Computing and Applications main idea of using cloud computing services for coordinating the work between multi-robot systems is not new, where before 2005 appeared what is called service-oriented architecture SOA [9], which is used to develop different robots such as Robotic Swarm robotics applications. Cloud robotics is a field of robotics that aims to use cloud technologies, services, and various cloud resources for robotics [10]. In this paper, we propose a new cloud system for managing swarm robot systems to perform multi-duty in real-time. The system makes robots benefit from cloud power via internet connection automatically without human interactions for controlling executed duties. The new system can be used to manage organizations that depend on robots, in a completely autonomous way. The contributions of the paper are as follows: • Proposing a new cloud multi-robot model. • Applying k-means to cluster all duties into groups. • Developing a new hybrid path planning algorithm based on the HHO algorithm and Nearest Neighbor algorithm to determine the best path. • Comparing the new algorithm with Genetic algorithms, simulated annealing algorithm, and traditional HHO algorithm. 2 Cloud multi-robot model and allocation problem Cloud computing platform is a common platform used for executing tasks and supplying various users with different kinds of computing services such as Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS), Robot applications as a Service (RaaS) and many new services are shown every day [11]. In this paper, we propose a new model called Cloud Multi-Robot Model CMRM (see Fig. 1). CSRM is used for managing the work between multi-robots remotely and over the internet using cloud computing. The main advantage of this model is that the processing takes place in the cloud platform instead of the robot controller. CMRM consists of seven components: robots, duties, data, the system, manager, cloud services, and virtual machines (VMS). We explain the function of each component below in detail. Multi-robot is a group of robots that work with each other to perform some duties. Robots and users send data over the internet to cloud management systems. The data sent contains robot location, robot specifications, number of duties, duty location, and duties description. A Cloud management system consists of an information system that is used for saving data. Furthermore, there is a pool of cloud services such as RaaS, SaaS, IaaS, and PaaS. The manager is the brain of the cloud management system. It is 123 responsible for sending data to VMs for processing and taking actions according to results. The main sim of the manager is to manage the robots. The manager can use some VMs for performing its tasks in parallel (Fig. 1). The multi-robot duty allocation (MRDA) problem is a problem of how multi-robots can be allocated to many duties for achieving a specific goal, where m robots are working together to carry out n duties. We can represent this problem as follows: A (...truncated)