With the emergence of Industry 4.0, high productivity is critically dependent on robot manipulators. However, building an efficient and safe work environment with robot manipulators remains a ...challenge of hardware capability. The optimal path planning of the robot manipulator usually encounters shortcomings in low computational speed and tedious training after changing assembly lines and increases the risk during human–robot collaboration (HRC). To solve such a problem, we propose a path planning, named slice-based heuristic fast marching tree, based on joint space to achieve real-time path planning speed without modeling or training the workspace in advance. Our experimental results indicate that the time consumed for path planning in static environments is only from 0.51 s to 1.63 s, tested by a 6-DOF general-purpose industrial manipulator and different cylindrical obstacle placements. The time for path replanning in dynamic environments is from 0.62 s to 0.88 s.
•Path planning is in 1.63 s with static obstacles and 0.88 s with dynamic obstacles.•The proposed path planning is faster, smoother, and shorter than RRT, RRT*, and FMT*.•The joint angles of revolutions in total are less than RRT, RRT*, FMT*.
In this paper, we proposed a novel multi-robot collaborative exploration method to improve the efficiency and robustness of multi-robot exploration in unknown environments. Firstly, a novel frontier ...detection algorithm based on hybrid multi-strategy rapidly-exploring random tree (HMS-RRT) is proposed, which is composed of an adaptive incremental distance strategy, a subregion sampling strategy and a greedy frontier-based exploration strategy. To improve the frontier detection performance of the algorithm, we adopt the Voronoi diagram to continuously partition the explored region, and dynamically adjust the incremental distance according to the density of obstacles in the subregions. To avoid the algorithm is trapped in the local optimum, we use Gaussian distribution to calculate the sampling probability in each subregion, so that the algorithm tends to sample in the subregion with lower crowded level of nodes and cover the unexplored regions quickly. Secondly, we introduce the greedy frontier-based exploration strategy to explore all Voronoi polygons in turn and refine the search results, meanwhile, the centroid of each frontier region is extracted as the exploration target point. Then, a multi-robot task assignment strategy based on improved market mechanism is introduced to dynamically assign the exploration target points to each robot, and the map-merging algorithm is used in the exploration process to merge several local maps in real-time. Finally, an experimental testing platform is developed based on Robot Operating System (ROS) and a series of experiments are carried out. The results show that our method can improve the efficiency and reliability of multi-robot exploration in both the simulations and the prototype experiments.
The manufacturing industry of the future requires innovative approaches to optimize operational efficiency and adaptability. Integrating context-awareness into workflow management systems has emerged ...as a promising avenue to enhance efficiency in modern manufacturing processes. This research presents an innovative context-aware workflow management architecture designed to address industry-related challenges and overcome current limitations in the state-of-the-art. The architecture leverages Industry 4.0 standards for asset representation and workflow notation while incorporating a Context Analyzer component for real-time context interpretation. The effectiveness of the proposed solution is demonstrated in a real-world manufacturing setting, specifically in the scenario of collecting work order materials using the Robot Operating System (ROS) technology for robot navigation. The evaluation showcases improvements in task completion rate, resource utilization, and task completion time. These outcomes exemplify the potential benefits of incorporating context-awareness into manufacturing workflows, providing insights for further improvements. Contributions include advancing the understanding of context-aware workflow management, a review of the challenges that cap its adoption in the manufacturing domain, a qualitative comparison of similar approaches, practical implementation of the proposed architecture, evaluation of the context-aware component, and provision of the source code and datasets to the community for future advancement and reproducibility.
•Advancing standardization of manufacturing processes with BPMN and AAS integration.•Enhancing manufacturing efficiency through context-aware workflow management.•ROS-based robots in a real-world manufacturing case study.•The proposed solution improved task completion rate, time, and energy saving.
Given the global population ages, the traditional medical system must change. Telemedicine combines the introduction of devices with sensors, software, and other Internet of Things technologies. ...Telemedicine is a new type of medical technology application. In this paper, we systematically integrate the force sensor, robot arm, optical radar device, and jelly mechanism to develop a telemedicine application system. We used a three-dimensional coordinate conversion formula to convert the coordinates of each axis of the robot arm into the coordinates of the smartphone so that the doctor can control the robot arm remotely using the smartphone. The force sensor embedded in the robot arm provides transparency to the doctor during operation, enabling them to monitor whether the force applied by the robotic arm on the human body is excessive. In addition, through the jelly mechanism installed on the robot arm, the doctor only needs to use a smartphone to control the jelly mechanism to achieve remote control needs. The experimental testing results sufficiently show the practicability of our scheme for telemedicine.
The application of efficient path planning algorithms for two-wheeled Autonomous Mobile Robots (AMRs) in static environments with obstacles is a significant challenge in robotics research. Existing ...methods, such as the A star (A*) algorithm utilized in Robot Operating System 2 (ROS2), can provide optimal paths but may have high computational complexity in intricate environments. This study explores the potential of three metaheuristic algorithms - Improved Particle Swarm Optimization (IPSO), Improved Grey Wolf Optimizer (IGWO), and Artificial Bee Colony (ABC) - for planning efficient and smooth paths in static environments. These algorithms are selected due to their ability to efficiently find near-optimal solutions and avoid local minima. In this study, the researchers designed and built a two-wheeled AMR using a Raspberry Pi 4 microcontroller as the main processing unit, working in conjunction with an Arduino Mega for controlling the DC motor drive through an MDD10A motor driver circuit. The robot is equipped with an RPLiDAR A1 sensor to read 360-degree distance values for mapping and obstacle avoidance. The experimental results clearly indicate that the metaheuristic algorithms, especially ABC, can calculate paths up to 7% shorter than A* while requiring only one-tenth of the time. Moreover, ABC demonstrates superior motion smoothness when applied to the actual two-wheeled robot in static environments. This work represents a significant step in developing algorithms for two-wheeled robots that are ready to support real-world operations in industries, logistics, healthcare, or various service sectors, which can help increase efficiency and reduce operating costs in the future.
•Developed MAs for efficient path planning of AMRs in ROS 2.•Tested IPSO, IGWO, and ABC algorithms on a custom-built, two-wheeled AMR prototype.•ABC outperformed A* with up to 7% shorter paths and 90% faster computation times.•ABC demonstrated superior motion smoothness, facilitating navigation in complex environments.
Energy consumption estimation and management of the maritime Unmanned Surface Vehicles (USV) is an important issue to deal with energy minimization techniques such as path planning, tasks scheduling, ...etc. In this paper, we introduce the energy consumption parameter in USV simulation through three contributions: 1) An analytic USV's energy consumption model is developed based on the three-degrees-of-freedom dynamic model of surface vessels. 2) A reverse engineering approach is proposed to identify the previously used dynamic model parameters based on a set of scenarios executed within a recent simulation environment. 3) The simulator engine is enriched with the consumption modelling tools such that the power absorbed by the USV is instantaneously calculated and returned; thus, the required energy of any predefined scenario is available as a new simulation result.
•The unmanned maritime drones' autonomy is limited by their battery capacities.•Several available approaches are used to reduce their consumption.•The existing solutions are not feasible in complicated environments or huge scenarios.•The problem is solved by developing a more realistic power model of the marine drones.•A robust simulator is used to manage and estimate the consumption of marine drones.
The autonomous driving industry has mushroomed over the past decade. Although autonomous driving has undoubtedly become one of the most promising technologies of this century, its development faces ...multiple challenges, of which security is the major concern. In this article, we present a thorough analysis of autonomous driving security. First, the attack surface of autonomous driving is presented. After an analysis of the operation of autonomous driving in terms of key components and technologies, the security of autonomous driving is elaborated in four dimensions: 1) sensors; 2) operating system; 3) control system; and 4) vehicle-to-everything (V2X) communication. Sensor security is examined from five components, which are mainly responsible for self-positioning and environmental perception. The analysis of operating system security, the second dimension, is concentrated on the robot operating system. Concerning the control system security, the controller area network is approached mainly from vulnerabilities and protection measures. The fourth dimension, V2X communication security, is probed from four categories of attacks: 1) authenticity/identification; 2) availability; 3) data integrity; and 4) confidentiality with corresponding solutions. Moreover, the drawbacks of existing methods adopted in the four dimensions are also provided. Finally, a conceptual multilayer defense framework is proposed to secure the information flow from external communication to the physical autonomous vehicle.
This paper is concerned with the first work on the integration of digital twin (DT), 5G, cloud platform, and virtual reality (VR) technologies for unmanned aerial vehicles (UAVs) autonomy ...development. DT focuses on connecting the virtual and physical world as an emerging strategic technology. Initially, it was implemented through mirror models of physical objects to realize the monitoring of their whole life cycle in the manufacturing area. In recent years, DT technologies have been applied in different fields, and some typical DT solutions have been proposed to solve complex system problems. In this paper, we study the problem of how to combine the DT and other emerging technologies for UAV autonomy development and supervision, aiming to propose a basic DT framework to integrate DT and UAVs as reference rules for building DT systems, which includes four parts, that is, Virtual Space, Real Space, Service Center, and Data and Model Processing Center. Based on the proposed basic DT framework, a cloud-based DT system is then further constructed in which cloud platform, 5G, and VR are integrated seamlessly. The running and implementation processes of each subsystem are introduced in detail. Multiple experiments are conducted to verify the usefulness of proposed DT system, that is, real-time system monitoring and cloud processing, VR connection, human–robot interaction through VR technology, and so on. The experimental results show that the proposed DTUAV system can be used in the interaction of virtual and physical systems, remote supervision, intelligence integration of swarm of unmanned vehicles, and so on. The development in our work introduces the DT into unmanned system applications and can promote relevant research in this direction. All implementation codes of the system will be shared in https://github.com/DTUAV.
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