Experimental studies on distributed control for area coverage using mobile robots

Having reliable wireless communication in a network of mobile robots is an ongoing challenge, especially when the mobile robots are given tasks in hostile or harmful environments such as radiation environments in scientific facilities, tunnels with large metallic components and complicated geometries as found at CERN. In this paper, we propose a decentralised method for improving the wireless network throughput by optimizing the wireless relay robot position to receive the best wireless signal strength using implicit spatial diversity concepts and gradient-search algorithms. We experimentally demonstrate the effectiveness of the proposed solutions with a KUKA Youbot omni-directional mobile robot. The performance of the algorithms is compared under various scenarios in an underground scientific facility at CERN.

Networked mobile robots are able to determine their poses (i.e., position and orientation) with the help of a well-configured environment with distributed sensors. Before localizing the mobile robots using distributed sensors, the environment has to have information on each of the robots’ prior knowledge. Consequently, if the environment does not have information on the prior knowledge of a certain mobile robot then it will not determine its current pose. To solve this restriction, as a preprocessing step for indoor localization, we propose a motion-based identification of multiple mobile robots using trajectory analysis. The proposed system identifies the robots by establishing the relation between their identities and their positions, which are estimated from their trajectories related to each of the paths generated as designated signs. The primary feature of the proposed system is the fact that networked mobile robots are quickly and simultaneously able to determine their poses in well-configured environments. Experimental results show that our proposed system simultaneously identifies multiple mobile robots, and approximately estimates each of their poses as an initial state for autonomous localization.

Wired computer networks are vital in modern life. However, these networks are extremely vulnerable to disaster or attack in emergency situations. Therefore, how to maintain communication link under emergency situations is very important. In this paper, we utilize a series of autonomous mobile slave robots which follow behind the lead robot and automatically stop where needed to maintain an ad hoc network for guaranteeing a link between the lead robot and its remote monitor/control station. To accomplish this target, an efficient communication protocol limitation mobile robots broadcast based on AODV (LMRB-AODV) is proposed for deployment in multi-robot system. After then the lead robot could carry service traffics to the monitor station under emergency situations through the communication link. At any instance, the lead robot has the ability to reclaim the relay robot(s) which are unneeded in the network to rejoin the convoy behind the lead robot and use it to extend the range of wireless communication when the radio frequency (RF) shortcuts are detected by the lead robot. All relay deployment and reclaiming strategy functions occur without the operator's involvement. Finally, we provide a comparative study of their performance in a number of different simulation environments. The results show that the proposed scheme is very efficient in maintaining communication link in wireless network.

The paper is concerned with the region tracking control problem of multiple nonholonomic mobile robot systems with collision avoidance. The peculiar characteristic of the proposed scheme is that a class of potential energy functions is chosen to form the desired target region constraining the robots for aggregation, and some local potential energy functions are selected to maintain collision avoidance among robots. Such that each mobile robot only needs to interact with their neighbors to realize the region tracking control task. Moreover, this paper provides a new analytical framework of region tracking control for a network of wheeled mobile robots, in which the integration of the system decomposition and sliding mode control method enables to convert the nonholonomic constraint problem of the controlled mobile robot system into a holonomic constraint problem. This provides a new approach to solving the mobile robot control problem. Theoretical analysis and numerical simulation results are given to validate the effectiveness of the proposed control scheme.

This paper deals with a cooperative object tracking with mobile robotic sensor network. The occlusion problem, which is one of the most important problems of mobile object tracking, will be solve with utilizing the mobile robotic sensor network. Additionally, the high quality information of the object can be observed, since the robotic sensor network can change observation formation their own way. On the other hand, to solve these problems the high cognitive capability and high intelligence sharing ability of robots are required. Consequently, we propose to use high intelligent group robot each of which can communicate with Peer-to-Peer communication. The self-deployment algorithm and network routing algorithm are developed as a base technic of mobile robotic sensor network. The validity of these proposed algorithms are shown by multihop teleoperation experiment. The architecture to share common perceptions which is necessary for cooperative work are proposed.

In this paper, we present coordination algorithms for an heterogeneous robotic group consisting of a mobile manipulator and a number of mobile sensing agents to cooperatively estimate a toxic field and trace its maximum point. In particular, we treat the mobile manipulator as a master machine and mobile sensing agents as slave machines such that, at the converged configuration, the end effector of the manipulator can reach the maximum point. The unknown field has been modeled by a network of radial basis functions and mobile robots are coordinated by flocking and gradient control algorithms based on their estimated fields. A simulation study demonstrates the validity of the proposed scheme in an industrial disaster or emergency scenario.Copyright © 2012 by ASME

The problem of area coverage in unknown environments is crucial in applications such as environmental monitoring, disaster response, and autonomous navigation. Traditional methods struggle to balance exploration, obstacle avoidance, and efficient coverage. In this paper, we propose a deep reinforcement learning-based multi-agent approach that optimizes coverage efficiency while adapting to unknown obstacles. We integrate a two-layer architecture, where the upper layer employs reinforcement learning for global path planning, while the lower layer handles local obstacle avoidance and movement execution. Experimental results demonstrate that our algorithm effectively converges in unknown environments and completes the area coverage task.

In this work the method of communication and maintenance of integrity of data in the decentralized network of autonomous mobile robots is suggested. The software and hardware feasibility of such method is proposed. For collective storage and maintain data integrity in decentralized group of mobile robots, the algorithm of checksum calculations is proposed. The local voting protocol is used for load balancing of mobile robots. For the programming implementation of the data communication, multi-agent technology is used. An ultra light, unmanned aerial vehicle (UAV) is considered as the mobile robot.

Decentralized control of a group of mobile robots for deployment in sweep coverage

The area coverage problem solution is one of the vital research areas which can benefit from swarm robotics. The greatest challenge to the swarm robotics system is to complete the task of covering an area effectively. Many domains where area coverage is essential include exploration, surveillance, mapping, foraging, and several other applications. This paper introduces a survey of swarm robotics in area coverage research papers from 2015 to 2022 regarding the algorithms and methods used, hardware, and applications in this domain. Different types of algorithms and hardware were dealt with and analysed; according to the analysis, the characteristics and advantages of each of them were identified, and we determined their suitability for different applications in covering the area for many goals. This study demonstrates that naturally inspired algorithms have the most significant role in swarm robotics for area coverage compared to other techniques. In addition, modern hardware has more capabilities suitable for supporting swarm robotics to cover an area, even if the environment is complex and contains static or dynamic obstacles.

This work studies the localization accuracy of a team of mobile robots that perform cooperative localization. We provide an analytical expression for the upper bound in positioning accuracy as a function of a weighted connectivity graph for the network of relative position measurements in the robot group. This network has a time-varying topology determined by the availability of relative position measurements between pairs of robots. The weights of the connectivity graph depend on (i) the odometric and orientation accuracy of each robot, and (ii) the accuracy of the robot tracker on each member of the team that measures its relative position with respect to other robots in the group. The theoretical results are validated by extensive simulations.

This paper deals with multi-objective behavior coordination and sensory networks based on fuzzy control for multiple mobile robots. In multi-objective behavior coordination, weights are assigned to basic behaviors and updated gradually according to the time series of sensory inputs. A robot with our behavior coordination can take a smooth action. The sensory network is the self-update mechanism of a sensory range in order to realize flexible control with a small number of control rules. Both methods have been successfully applied to a single mobile robot. In this paper, we focus on an environment including multiple mobile robots. We examine the effects of the values for updating behavior weights and sensory ranges on the performance of multiple mobile robots. From the experimental results, we show the effectiveness of the multi-objective behavior coordination and sensory networks in the environment including multiple mobile robots.

The area coverage problem is an important issue because it can minimize uncertainty in a complex and unknown environment. This paper adopts a distributed anti-flocking algorithm inspired by the social behavior of solitary animals, which enables self-organized collaboration of multiple unmanned aerial vehicles (multi-UAVs) to achieve effective coverage of the mission area. The designed area coverage map represents the historical coverage information of each unmanned aerial vehicle (UAV). According to the rules of collision avoidance, decentering, and selfishness in the distributed anti-flocking algorithm, the UAVs are guided to move towards the direction that maximizing the coverage area and try to reduce the overlap of coverage region as well. Simulations show that the algorithm can achieve approximate full coverage of the task area and has good scalability, adaptability, and robustness.

This article studied the attacks that can be implemented in a network of mobile robots. The peculiarity of these attacks is that they, as a rule, use the vulnerabilities of wireless data transmission and the weakness of network protocols. The study was carried out using a simulation model of a group of mobile robots. It was modeled following attacks: denial of service, Black-Hole, Gray-Hole. In this case, it was analyzed the impact of the attacks on the energy consumption and the impact on network traffic. It was assessed the complexity of the implementation of various types of attacks. This analysis should make it clear with what intensity the attack should be conducted in order to damage the network. Also in this study, a method is proposed for calculating the trust of network nodes and the entire network as a whole based on the number of discarded packets.

Recently, the concept of behavioral media using a mobile robot has emerged in tele-robotics, where the mobile robot behaves as a user's second body or an agent in a remote site. An important issue in behavioral media is how to control the robot intuitively immersing a user into a remote site. This paper describes a new approach which combines locomotion interface and immersive projection display of a remote site for controlling a networked mobile robot. We have developed a prototype system and have evaluated the usability of the system with experiments.