Search

In response to the shortage of skilled workers and the increasing diversity of products and variants, integrating adaptive and flexible mobile manipulators into line-less mobile assembly systems (LMAS) stands out as a promising solution. To fully benefit from these robotic systems in LMAS, offloading computationally intensive tasks from mobile manipulators to edge computing systems is essential. This offloading of computational tasks not only lightens the processing load on individual robots but also enhances AI based perception, improving the overall system capabilities in dynamic manufacturing environments. Achieving these goals requires a robotic edge computing framework that serves as the key to flexible and adaptive mobile manipulation in LMAS. To construct such an edge computing framework, a comprehensive set of building blocks is required. These building blocks include a powerful edge system with high processing power, sensor-equipped mobile manipulators with the ability to perceive the environment, and a robust edge-to-robot connectivity. A comprehensive software stack, including software modules for localization and navigation in dynamic assembly environments, AI perception for precise pose estimation of assembly components, and motion planning for interaction between manipulators and assembly components, is crucial. Furthermore, virtualization techniques, a comprehensive deployment strategy, and a detailed description of robot hardware, site, and resources are essential. The proposed edge computing framework presents a solution that addresses mobile manipulators in LMAS and paves the way towards advanced industrial automation. Through implementation in a research assembly environment, the realized proof-of-concept showcased the feasibility of the proposed edge computing framework in a real-world pick-and-place scenario, highlighting its potential to enhance adaptivity and flexibility. There is a potential to refine and expand the framework to accommodate a broader range of industrial applications and streamline diverse manufacturing processes through the integration of mobile manipulators and edge computing within industrial settings. [ABSTRACT FROM AUTHOR]

Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This work describes the development of a tool for the teleoperation of robots. The tool is developed in a virtual environment using the Unity graphics engine. For the development of the application, a kinematic model and a dynamic model of a mobile manipulator are used. The mobile manipulator robot consists of an omnidirectional platform and an anthropomorphic robotic arm with 4 degrees of freedom (4DOF). The model is essential to emulate the movements of the robot and to facilitate the immersion in the virtual environment. In addition, the control algorithms are established and developed in MATLAB 2020 software, which improves the acquisition of knowledge to teleoperate robots and execute tasks of manipulation and transport of objects. This methodology offers a cheaper and safer alternative to real physical systems, as it reduces both the costs and risks associated with using a real robot for training. [ABSTRACT FROM AUTHOR]

A tool for path following for a mobile manipulator is herein presented. The control algorithm is obtained by projecting a local frame associated with the robot onto the desired path, thus obtaining a non-orthogonal moving frame. The Serret–Frenet frame moving along the curve is considered as a reference. A curve resulting from the control points of a B-spline in 2D or 3D is investigated as the desired path. It is used to show how the geometric continuity of the path has an impact on the performance of the robot in terms of undesired force spikes. This can be understood by looking at the curvature and, in 3D, at the torsion of the path. These unwanted effects vanish and better performance is achieved thanks to the change of the B-spline order. The theoretical results are confirmed by the simulation study for a mobile manipulator consisting of a non-holonomic wheeled base coupled with a holonomic robotic arm with three degrees of freedom (rotational and prismatic). [ABSTRACT FROM AUTHOR]

Recently, research has been conducted on mixed reality (MR), which provides immersive visualization and interaction experiences, and on mapping human motions directly onto a robot in a mixed reality (MR) space to achieve a high level of immersion. However, even though the robot is mapped onto the MR space, their surrounding environment is often not mapped sufficiently; this makes it difficult to comfortably perform tasks that require precise manipulation of the objects that are difficult to see from the human perspective. Therefore, we propose a system that allows users to operate a robot in real space by mapping the task environment around the robot on the MR space and performing operations within the MR space. [ABSTRACT FROM AUTHOR]

Explosive ordnance disposal (EOD) operations are hazardous due to the volatile and sensitive nature of these devices. EOD robots have improved these tasks, but their high cost limits accessibility for security institutions that do not have sufficient funds. This article presents the design, implementation, and validation of a low-cost EOD robot named JVC-02, specifically designed for use in explosive hazardous environments to safeguard the safety of police officers of the Explosives Disposal Unit (UDEX) of Arequipa, Peru. To achieve this goal, the essential requirements for this type of robot were compiled, referencing the capabilities of Rescue Robots from RoboCup. Additionally, the Quality Function Deployment (QFD) methodology was used to identify the needs and requirements of UDEX police officers. Based on this information, a modular approach to robot design was developed, utilizing commercial off-the-shelf components to facilitate maintenance and repair. The JVC-02 was integrated with a 5-DoF manipulator and a two-finger mechanical gripper to perform dexterity tasks, along with a tracked locomotion mechanism, which enables effective movement, and a three-camera vision system to facilitate exploration tasks. Finally, field tests were conducted in real scenarios to evaluate and experimentally validate the capabilities of the JVC-02 robot, assessing its mobility, dexterity, and exploration skills. Additionally, real EOD missions were carried out in which UDEX agents intervened and controlled the robot. The results demonstrate that the JVC-02 robot possesses strong capabilities for real EOD applications, excelling in intuitive operation, low cost, and ease of maintenance. [ABSTRACT FROM AUTHOR]

Mobile Manipulators (MoMa) is a category of mobile robots designed to assist people with motor disabilities to perform object retrieval tasks using a webcam-based gaze control system. Using off-the-shelf components such as reproducible acrylic and 3D-printed plates, and a webcam for eye tracking, MoMa serves as an inexpensive, open-source, and customizable solution in assistive robotics. The robotic system consists of a mobile base that can move forward and backward, as well as turn in place; and a 2-axis cartesian arm equipped with a claw gripper that opens and closes. The simple movement of the robot also allows for a simple control method and graphical user interface (GUI). The user receives information about what is in front of the robot through a mounted camera, and, by looking at parts of the screen that correspond to controls, has their gaze predicted by a convolutional neural network and sends commands wirelessly. The performance of the entire system has been validated through testing of the gaze prediction model, the integration of the control system, as well as its task completion capabilities. All the design, construction and software files are freely available online under the CC BY 4.0 license at https://doi.org/10.17632/k7yfn6wdv7.2.

Research on trajectory tracking control for climbing welding robots holds significant importance in the field of automated welding. However, existing trajectory tracking methods suffer from issues such as jitter and slow speed. In this paper, an improved sliding mode control strategy is proposed based on the self-designed wall-climbing welding mobile manipulator. Firstly, a new adaptive sliding mode control strategy is proposed for the mobile platform based on the kinematic model. By introducing a new approach law, the controller is designed when the distance between the center of mass is unknown. Secondly, regarding the manipulator, we analyze simplified dynamic equations, extract uncertain components, and utilize a CNN for compensation. This compensation strategy is integrated into the sliding mode control law, achieving precise control over the manipulator and effectively resolving issues like slow tracking speeds, large errors, and chattering. The stability of the robot control system is proved by the Lyapunov function. Through simulation analysis and experimental validation, the proposed control method is confirmed to be feasible and superior. [ABSTRACT FROM AUTHOR]

This paper represents a constraint planning and optimization control scheme for a highly redundant mobile manipulator considering a complex indoor environment. Compared with the traditional optimization solution of a redundant manipulator, infinity norm and slack variable are additionally introduced and leveraged by the optimization algorithm. The former takes into account the joint limits effectively by considering individual joint velocities and the latter relaxes the equality constraint by decreasing the infeasible solution area. By using derived kinematic equations, the tracking control problem is expressed as an optimization problem and converted into a new quadratic programming (QP) problem. To address the optimization problem, the two-timescale recurrent neural networks optimization scheme is proposed and tested with a 9 DOFs nonholonomic mobile-based manipulator. Additionally, the B I 2 R R T ∗ path-planning algorithm incorporates path planning in the complex environment where different obstacles are positioned. To test and evaluate the proposed optimization scheme, both predefined and generated paths are tested in the Neurorobotics Platform (NRP) 2 2 https://neurorobotics.net. which is open access and open source integrative simulation framework powered by Gazebo and developed by our team. • The kinematic model of a 9 DOFs mobile-based manipulator is derived. • The tracking control problem with infinity norm and slack variable is formulated. • A two-timescale recurrent neural (TNN) networks optimization scheme is introduced • TNN addresses the hierarchical optimization problem with planning trajectory. • The experiments using B I 2 R R T ∗ are demonstrated in Neurorobotics platform. [ABSTRACT FROM AUTHOR]

Mobile manipulators find versatile applications across various fields, leveraging the combination of autonomous functionalities and bilateral teleoperation schemes to enhance the effectiveness of these robotic mechanisms. Regarding teleoperation, command generation involves a leader robot with a few degrees of freedom in a bounded workspace, accompanied by a redundant follower robot operating in an unbounded workspace. This article introduces the concept of Cartesian/articular control for delayed bilateral teleoperation of a mobile manipulator, where the follower robot aims to execute the rate/nonlinear-position commands issued by a human handling the leader robot through a proposed hybrid mapping. We implement a P+d controller applied in Cartesian space for the leader while a controller based on inverse kinematics in joint space is employed for the follower, taking advantage of its redundancy. We then propose a Lyapunov–Krasovskii candidate function to analyze theoretically and numerically the time derivative of the functional on the system trajectories. As a result, we derive the conditions that the proposed hybrid mapping and controller parameters must satisfy to ensure bounded errors. Finally, we statistically evaluated objective metrics from multiple pick-and-place task executions considering time delays to quantify the performance achieved.

Door-traversal research has been intensively studied. The challenge of the door traversal problem is derived from the requirement of the mobile manipulator robot to regulate the position of its end-effector while moving along a path. This research presents the door traversal of a mobile manipulator robot by simulating the work environment in the Gazebo program, using the Behavior Trees (BT) architecture to decide on various tasks with complex behaviors to manipulate the open and closed-door conditions. This study developed a program using Robot Operating System (ROS2) as middleware to connect different parts of the program. The results of this research show that classical BT still have limitations in the case of robot positioning errors, resulting in the possibility of BT making incorrect decisions. To overcome these limitations, the robot must be able to learn and comply with the errors. However, experiments have shown many advantages of BT, including flexibility in creating complex behaviors, easy understanding of work steps, decision-making processes, and maintenance capabilities that make it easy to modify robot behavior. As a result, we successfully created robot behaviors using BT to address the door traversal problem, encompassing both door opening and closing scenarios. Furthermore, we identified the limitations of position errors affecting the output of the BT.

Motion planning for mobile manipulators is challenging because of their high degrees of freedom. The most effective approach for the motion planning of a mobile manipulator is to consider the different characteristics of a mobile robot and a manipulator while planning and controlling each system separately. In a previous study, different characteristics were considered using virtual impedance. This method involves forming a virtual impedance relationship between the two subsystems, enabling the mobile robot to track the movement of the manipulator. However, this study had certain limitations. Firstly, this method is not applicable to non-holonomic mobile robots. Secondly, obstacle avoidance methods for mobile robots are not considered. To address these limitations, our study proposes a novel concept for our motion planner that is called the virtual impedance energy field (VIEF), which refers to the work and change in total energy. We solved the first limitation of the previous study by transforming the virtual impedance force into the VIEF. Moreover, by integrating an obstacle field with the VIEF and using it as a local costmap, the second limitation was addressed. To validate the performance of our motion planner, we conducted simulations in environments comprising obstacles, with straight and curved trajectories of the end-effector. We then analyzed the pose change graph of the mobile robot and end-effector, pose error of the end-effector, and velocity of the mobile robot. We therefore confirmed that the manipulator successfully followed the desired trajectory, while the mobile robot maintained a distance from the end-effector and avoided obstacles.

Interactive robots that cooperate with humans must take appropriate actions in response to their requests. Unfortunately, such requests often have information gaps with their actual demands. However, robots are still expected to reason and act on what is required, depending on the situation. We call these reflective actions. To achieve such reflective actions for robots, we constructed a dataset that consists of the reflective actions of a domestic manipulation robot, in which the actions correspond to user utterances with their surroundings situations. By crowdsourcing, we defined several action scenarios that could be regarded as reflective. We recorded videos of situations described in the crowdsourcing scenarios, corresponding to the user situations just before the robot’s reflective actions. We also annotated the videos of the user utterance transcriptions, objects, user poses, and user positions to investigate the contribution of such descriptive features to the reflective action decisions. Our experimental results indicated that even though our newly defined task is very challenging, it can be solved if the system has a concrete understanding of the situation.

A tool for path following for a mobile manipulator is herein presented. The control algorithm is obtained by projecting a local frame associated with the robot onto the desired path, thus obtaining a non-orthogonal moving frame. The Serret–Frenet frame moving along the curve is considered as a reference. A curve resulting from the control points of a B-spline in 2D or 3D is investigated as the desired path. It is used to show how the geometric continuity of the path has an impact on the performance of the robot in terms of undesired force spikes. This can be understood by looking at the curvature and, in 3D, at the torsion of the path. These unwanted effects vanish and better performance is achieved thanks to the change of the B-spline order. The theoretical results are confirmed by the simulation study for a mobile manipulator consisting of a non-holonomic wheeled base coupled with a holonomic robotic arm with three degrees of freedom (rotational and prismatic).

In this paper, a new approach involving the use of a mobile manipulator to assist humans with mobility impairments to walk is proposed. First, in order to achieve flexible interaction between humans and mobile manipulators, we propose a variable admittance controller that can adaptively regulate the virtual mass and damping parameters based on the interaction forces and the human motion intention predicted using the fuzzy theory. Moreover, a feedforward velocity compensator based on a designed state observer is proposed to decrease the inertia resistance of the manipulator, effectively enhancing the compliance of the human–robot interaction. Then, the configuration of the mobile manipulator is optimized based on a null-space approach by considering the singularity, force capacity, and deformation induced by gravity. Finally, the proposed assisted walking approach for the mobile manipulator is implemented using the human–robot interaction controller and the null-space controller. The validity of the proposed controllers and the feasibility of assisted human walking are verified by conducting a set of tests involving different human volunteers. [ABSTRACT FROM AUTHOR]

This paper explores the qualification of a digital twin (DT) for a mobile manipulator (MOMA) in industrial applications. We discuss the development of different DT models based on various industrial needs and highlight the dependence of model accuracy on online sensor precision. Limitations of DTs for MOMA are examined, including challenges in respecting qualifiers due to the inability to incorporate unstructured aspects of the factory environment. Through a case study and some examples, we show the latent potential and limitations of DTs for MOMA in industrial contexts. The challenges of fidelity, real-time operation, and environment modeling are discussed. It is emphasized that creating a true digital twin of a mobile manipulator is hindered by the inability to include the complete surrounding environment. Recommendations for future research focus on addressing these limitations to enhance the effectiveness of DTs for MOMA in Industry 4.0 and smart manufacturing. [ABSTRACT FROM AUTHOR]

The demand for liquefied natural gas (LNG) ships is increasing for various reasons. Despite their enormous size, cargo holds inside freighters transporting LNG have traditionally been constructed by welding to high-quality standards for safety. This process traditionally relies on manual labor or semi-automatic moving devices. In this study, a methodology was designed for robot-based automated laser welding inside large LNG cargo holds. The developed approach offers a practical solution to challenging issues such as the corrugation of the membrane that forms the inner walls of LNG cargo holds and the inter-floor movement of robots. This study analyzes and restructures the work for laser welding using mobile robots inside LNG cargo holds composed of membranes. For realistic constraints, such as inter-floor movement of robots and high-quality welding of membrane corrugations, methods integrated with manual work have been proposed. Additionally, for the overall membrane laser welding of the LNG cargo hold space, an automated method using robots was suggested. The developed methodology has been realized as operational software for the movement of robots for laser welding in LNG cargo holds. [ABSTRACT FROM AUTHOR]

The coupling effects of mobile manipulators on the motion characteristics of mobile platforms during the dynamic operation process, would increase the complexity and nonlinearity of the whole system and then bring great challenges to the system modelling. A new hierarchical aggregation modelling method was proposed to solve this issue. The method is based on the hierarchical properties of the Udwadia-Kalaba (UK) theory in the analytical mechanics. First, the mobile manipulator was divided into 3 subsystems, and the unconstrained dynamics of each one was modelled with the Lagrangian equations. Subsequently, the basic Udwadia-Kalaba equations (UKE) were employed to model the overall system, in view of the constraints within the mechanical structure of the mobile manipulator. In addition, the Lyapunov stability-based theory was used to compensate for the initial condition deviations to achieve convergence of the ideal trajectory. Simulation results validate the feasibility of the proposed modelling method. [ABSTRACT FROM AUTHOR]

This study achieved four door operations, namely push-opening, push-closing, pull-opening, and pull-closing movements, using a mobile manipulator consisting of a commercially available arm robot and a mobile robot. We assumed that the arm robot is controlled by position commands at intervals of a few milliseconds, and that the mobile robot is guided by a simple straightforward linear trajectory. Ott, Borst, Bäuml, and Hirzinger proposed a push-opening method using impedance control in a cylindrical coordinate system for the arm robot. With this control, when the mobile robot advances toward and through the door, the arm robot moves passively and properly pushes the door open. However, their method is unsuitable for the above type of robot. Thus, we propose a method with two modifications: the use of admittance control and the improvement of force relaxation by considering a force obtained through a novel force decomposition. Furthermore, the proposed method was demonstrated not only in the push-opening movement but also in the push-closing, pull-opening, and pull-closing movements. [ABSTRACT FROM AUTHOR]

This work describes the development of a tool for the teleoperation of robots. The tool is developed in a virtual environment using the Unity graphics engine. For the development of the application, a kinematic model and a dynamic model of a mobile manipulator are used. The mobile manipulator robot consists of an omnidirectional platform and an anthropomorphic robotic arm with 4 degrees of freedom (4DOF). The model is essential to emulate the movements of the robot and to facilitate the immersion in the virtual environment. In addition, the control algorithms are established and developed in MATLAB 2020 software, which improves the acquisition of knowledge to teleoperate robots and execute tasks of manipulation and transport of objects. This methodology offers a cheaper and safer alternative to real physical systems, as it reduces both the costs and risks associated with using a real robot for training.

Recently, research has been conducted on mixed reality (MR), which provides immersive visualization and interaction experiences, and on mapping human motions directly onto a robot in a mixed reality (MR) space to achieve a high level of immersion. However, even though the robot is mapped onto the MR space, their surrounding environment is often not mapped sufficiently; this makes it difficult to comfortably perform tasks that require precise manipulation of the objects that are difficult to see from the human perspective. Therefore, we propose a system that allows users to operate a robot in real space by mapping the task environment around the robot on the MR space and performing operations within the MR space.

Explosive ordnance disposal (EOD) operations are hazardous due to the volatile and sensitive nature of these devices. EOD robots have improved these tasks, but their high cost limits accessibility for security institutions that do not have sufficient funds. This article presents the design, implementation, and validation of a low-cost EOD robot named JVC-02, specifically designed for use in explosive hazardous environments to safeguard the safety of police officers of the Explosives Disposal Unit (UDEX) of Arequipa, Peru. To achieve this goal, the essential requirements for this type of robot were compiled, referencing the capabilities of Rescue Robots from RoboCup. Additionally, the Quality Function Deployment (QFD) methodology was used to identify the needs and requirements of UDEX police officers. Based on this information, a modular approach to robot design was developed, utilizing commercial off-the-shelf components to facilitate maintenance and repair. The JVC-02 was integrated with a 5-DoF manipulator and a two-finger mechanical gripper to perform dexterity tasks, along with a tracked locomotion mechanism, which enables effective movement, and a three-camera vision system to facilitate exploration tasks. Finally, field tests were conducted in real scenarios to evaluate and experimentally validate the capabilities of the JVC-02 robot, assessing its mobility, dexterity, and exploration skills. Additionally, real EOD missions were carried out in which UDEX agents intervened and controlled the robot. The results demonstrate that the JVC-02 robot possesses strong capabilities for real EOD applications, excelling in intuitive operation, low cost, and ease of maintenance.

In industry, mobile manipulators are commonly used to perform various tasks. However, current mobile manipulator motion planning still poses significant challenges due to the scalability of the manipulator motion planning, the non-holonomic nature of the mobile base, and the need to coordinate the motion of the manipulator and mobile base. Considering the accuracy disparity between the mobile base and manipulator, this paper proposes a joint space coordination scheme for mobile manipulators to improve the execution quality of the end-effector trajectory obtained by learning from demonstrations in the task space. Additionally, a task-oriented manipulability is developed to further enhance the execution accuracy. The results of extensive simulations are presented to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper focuses on motion planning for mobile manipulators, which includes planning for both the mobile base and the manipulator. A hierarchical motion planner is proposed that allows the manipulator to change its configuration autonomously in real time as needed. The planner has two levels: global planning for the mobile base in two dimensions and local planning for both the mobile base and the manipulator in three dimensions. The planner first generates a path for the mobile base using an optimized A* algorithm. As the mobile base moves along the path with the manipulator configuration unchanged, potential collisions between the manipulator and the environment are checked using the environment data obtained from the on-board sensors. If the current manipulator configuration is in a potential collision, a new manipulator configuration is searched. A sampling-based heuristic algorithm is used to effectively find a collision-free configuration for the manipulator. The experimental results in simulation environments proved that our heuristic sampling-based algorithm outperforms the conservative random sampling-based method in terms of computation time, percentage of successful attempts, and the quality of the generated configuration. Compared with traditional methods, our motion planning method could deal with 3D obstacles, avoid large memory requirements, and does not require a long time to generate a global plan. [ABSTRACT FROM AUTHOR]

An output feedback trajectory tracking control scheme for nonholonomic mobile manipulator robot systems with full-output constraints is presented in this article. Different from the previous methods, the kinematic model of the system is transformed into a special chained form by a rotation-like matrix. A globally exponentially stable speed observer with generalized dynamic scaling function is constructed to obtain the velocity estimation of the system. The output feedback tracking constrained controller is successfully constructed by Barrier Lyapunov function, backstepping and the excellent observer, which considering the system dynamics and the full-output constraints is achieved with only measurable outputs. [ABSTRACT FROM AUTHOR]

With the rapid development of science and technology, the current ordinary industrial manipulator cannot complete the task well, because it is difficult to control. This research mainly discusses the planning and control of the mobile manipulator for the operation of restricted motion objects in an intelligent environment. In this study, the rapid search random tree (RRT) method is used to study the obstacle avoidance motion planning of the manipulator. The 6-axis robotic arm system uses CAN (controller area network) bus to connect each joint in series and then connect to the multi-axis controller Maestro, and the host computer and Maestro send and receive control commands based on the TCP/IP protocol. A 1-DOF grip is installed at the end of the robotic arm, and the grip is connected to the end of the robotic arm (i.e., at the wrist joint of the robotic arm) through a 6-dimensional force 1 torque sensor. The operating system of the host computer is Ubuntu 14.04. The position of the object is recognized through Kinect, and the position of the object is sent to the robotic arm control software. The PTP (precision time protocol) of the robotic arm moves to a certain distance in front of the object, and then the movement of the robotic arm is controlled by visual servoing to complete the object capture. Each joint of the manipulator uses a speed control mode. In a single control cycle, the joint angular velocity of the manipulator remains unchanged. The controller used by the robotic arm is a 51-core STC12C5410AD single-chip microcomputer, which ensures the response speed of the joint motor linkage. In the environment of multiple obstacles, the RRT algorithm has 10 simulation experiments, the average sampling time is 95.651 s, and the average sampling point is 1308. The results show that the RRT algorithm proposed in this study enables the manipulator to move from the starting point to the endpoint in the environment of multiple obstacles, while avoiding the obstacles, and the mobile manipulator can better operate the motion-limited objects. [ABSTRACT FROM AUTHOR]

Inspection and repair interventions play vital roles in the asset management of railways. Autonomous mobile manipulators possess considerable potential to replace humans in many hazardous railway track maintenance tasks with high efficiency. This paper investigates the prospects of the use of mobile manipulators in track maintenance tasks. The current state of railway track inspection and repair technologies is initially reviewed, revealing that very few mobile manipulators are in the railways. Of note, the technologies are analytically scrutinized to ascertain advantages, unique capabilities, and potential use in the deployment of mobile manipulators for inspection and repair tasks across various industries. Most mobile manipulators in maintenance use ground robots, while other applications use aerial, underwater, or space robots. Power transmission lines, the nuclear industry, and space are the most extensive application areas. Clearly, the railways infrastructure managers can benefit from the adaptation of best practices from these diversified designs and their broad deployment, leading to enhanced human safety and optimized asset digitalization. A case study is presented to show the potential use of mobile manipulators in railway track maintenance tasks. Moreover, the benefits of the mobile manipulator are discussed based on previous research. Finally, challenges and requirements are reviewed to provide insights into future research. [ABSTRACT FROM AUTHOR]

Mobile manipulator robots have become important pieces of equipment due to the high mobility of mobile subsystems and the high flexibility of manipulator subsystems. Considering the increasing degrees of freedom and the need to avoid singular locations, one of the most challenging problems is solving the inverse kinematics problem of mobile manipulator robots (IKMM). Of all the popular optimization algorithms, the differential evolution (DE) algorithm is the most effective method for quickly solving the IKMM problem with sufficient solutions. Currently, many strategies have been proposed for DE algorithms to improve the performance of solving mathematical problems; some symmetry strategies or symmetry functions have been introduced to DE algorithms. However, the effects of various DE algorithms on solving the actual IKMM lack a comprehensive explanation. Therefore, we divide various DE algorithms into three categories considering the control parameter selection and compare the specific optimization of various DE algorithms. Then, we compare the performance of various DE algorithms when solving the inverse kinematics problems of mobile manipulators with different degrees of freedom. Considering the effectiveness and the speed of the DE algorithm on the IKMM problem, we determine the best DE algorithm by comparing the error and time required to reach 100 random mission points and tracking the typical trajectories. Finally, the best-performing DE method is further improved by studying the selection of fundamental parameters in the best DE algorithm. Valuable conclusions are obtained from these experimental simulations, which can help with choosing an algorithm that is suitable for solving the inverse kinematics problem of mobile manipulator robots in practice. [ABSTRACT FROM AUTHOR]

The mobile manipulator is a relatively recent development in the robotics domain. It is a type of robot system that extends the manipulation capabilities of a robotic arm by the mobility capabilities of a mobile platform. As a result, mobile manipulators promise to provide a wider usage of manipulators (for example, by extending their reach) and to enable automation of use cases that are still manually performed. They can, for instance, automate repetitive tasks, freeing human workers to focus on more valuable tasks. They can also be deployed to perform dangerous or difficult tasks, reducing the risk of workplace injuries. Additionally, using mobile manipulators can help meet the growing demand for fast and flexible production processes, enabling them to better compete in a rapidly changing market. However, integrating these systems bears complexity, high acquisition costs, and unsolved safety and security challenges. Therefore, this new approach is only beginning to be adopted in the manufacturing industry. Especially small and medium-sized companies (SMEs) suffer from these challenges, as they usually have fewer resources. However, mobile manipulators are a valuable tool to enhance their competitiveness and profitability in various industries. In order to unleash these benefits, this paper provides a comprehensive review of application cases of mobile manipulators within smart factory setups. It focuses on specific requirements and advantages for SMEs. [ABSTRACT FROM AUTHOR]