Search Results (51)

The developed omnidirectional mobile manipulator is an educational omnidirectional mobile manipulator that utilizes the Raspberry Pi Pico W and is programmed in Python. It is designed to enhance STEM education by providing an interactive environment for studying robotics, sensor integration, and programming techniques. The robot is built on an off-the-shelf chassis equipped with Mecanum wheels and a robotic arm actuated by servo motors. As part of this project, the control electronics were designed and implemented to enable seamless operation. While the platform allows students to program the robot as part of the STEM curriculum, our base software solution, developed in Python, provides control of both the mobile base and the robotic arm via a web interface accessible through the robot’s Wi-Fi hotspot. Full article

Robotic walking assistance devices support the rehabilitation of patients with neurological impairments. However, most commercialized systems rely on treadmill-based walking, which may not reflect real-world environments. This study aimed to evaluate the usability of a newly developed over-ground walking assistance robot (OWAR-MW) based on mecanum wheels compared with a commercial system (Andago) from the perspectives of physical therapists and patients with stroke. Nine physical therapists and nine stroke patients participated. Each participant walked 100 m using both the OWAR-MW and Andago systems. Subsequently, a satisfaction survey was conducted across three categories—safety, operability and functionality, and convenience—using a questionnaire adapted from the standard usability testing guidelines for walking assistive devices. Additionally, in-depth interviews were conducted to explore user experience and improvement needs. In both participant groups, the OWAR-MW showed a tendency for lower satisfaction scores than Andago across all categories. Stroke patients reported significantly lower scores in all three categories (safety: 4.90 vs. 4.04, operability and functionality: 4.83 vs. 4.33, convenience: 4.87 vs. 4.49, p < 0.05), whereas therapists noted a significant difference only in safety (4.02 vs. 3.37, p < 0.05). Key issues identified included a lack of handles, delay in actuator response, low motion detection sensitivity, non-intuitive controls, and discomfort caused by the harness, particularly the thigh straps. OWAR-MW demonstrated usability limitations in its current prototype form. Technical improvements in user interface, control accuracy, and harness design are necessary before clinical application. This study provides valuable feedback for the future development of user-centered rehabilitation robotics. Full article

Mecanum and omni wheel-based assistive technologies present an alternative to conventional mobility devices for individuals with motor impairments, owing to their omnidirectional movement capabilities and high maneuverability in constrained environments. This systematic review identifies and categorizes the key challenges and emerging trends in the development of such systems. Primary obstacles include limited stability and maneuverability on uneven terrain, high energy consumption, complex control requirements, and elevated production costs. In response, recent studies have introduced several innovative approaches, such as advanced suspension systems to enhance terrain adaptability, modular mechanical designs to reduce manufacturing complexity, energy-efficient motor control strategies such as field-oriented control, AI-driven autonomous navigation, and hands-free user interfaces—including gesture recognition and brain–computer interfaces. By synthesizing findings from 26 peer-reviewed studies, this review outlines current technical limitations, surveys state-of-the-art solutions, and offers strategic recommendations to inform future research in intelligent assistive mobility technologies. Full article

This study proposes a novel nonlinear adaptive fuzzy hybrid sliding mode (AFHSM) control strategy for the precise trajectory tracking of autonomous mobile robots (AMRs) equipped with four Mecanum wheels. The control design addresses the inherent complexities of such platforms, which include strong system nonlinearities, significant parametric uncertainties, torque saturation effects, and external disturbances that can adversely affect dynamic performance. Unlike conventional approaches that rely on model linearization or dimension reduction, the proposed AFHSM control retains the full nonlinear characteristics of the system to ensure accurate and robust control. The controller is systematically derived from the trajectory-tracking error dynamics between the AMR and the desired trajectory (DT). It integrates higher-order sliding mode (SM) control, fuzzy logic inference, and adaptive learning mechanisms to enable real-time compensation for model uncertainties and external perturbations. In addition, a saturation handling mechanism is incorporated to ensure that the control signals remain within feasible limits, thereby preserving actuator integrity and improving practical applicability. The stability of the closed-loop nonlinear system is rigorously established through the Lyapunov theory, guaranteeing the asymptotic convergence of tracking errors. Comprehensive simulation studies conducted under severe conditions with up to 60 percent model uncertainty confirm the superior performance of the proposed method compared to classical SM control. The AFHSM control consistently achieves lower trajectory and heading errors while generating smoother control signals with reduced torque demand. This improvement enhances tracking precision, suppresses chattering, and significantly increases energy efficiency. These results validate the effectiveness of the AFHSM control approach as a robust and energy-aware control solution for AMRs operating in highly uncertain and dynamically changing environments. Full article

This paper investigates the dynamic modeling and robust control of a Mecanum-wheeled vehicle (MWV) under load disturbances and measurement noise. The system is modeled as a cascaded state-space representation, where the motor transfer function (PWM input → torque output) and the vehicle transfer function (torque input → vehicle speed output) are combined. The PWM-induced motor delay is linearized, and the complete dynamic model is derived using Lagrangian mechanics, addressing the limitations of conventional models that are incomplete and unable to decouple control signals from disturbance signals. For the developed model, a robust stability controller is designed by integrating Internal Model Control (IMC) with a Disturbance Observer (DOB), enhancing real-time disturbance rejection. Open-loop experiments validate the model’s accuracy, showing a Dynamic Time Warping (DTW) error of 0.2662 m, significantly lower than the 0.3198 m observed in traditional models. In closed-loop simulations, under load disturbances ($T_L=0.1$ to $T_L=-0.7$) and Gaussian noise (power: 0.0001–0.00005), the proposed IMC + DOB controller achieves 97.6% faster stabilization than IMC and 98.3% faster than PID, demonstrating superior convergence speed, robustness, and disturbance rejection. This study provides a novel control strategy that effectively handles non-square system dynamics while mitigating external disturbances in real time. The proposed framework enhances trajectory tracking accuracy and stability, with potential applications in autonomous robotics and vehicular systems. Full article

Wheelchairs play a crucial role in society by providing mobility and autonomy to individuals with physical disabilities, essential for their social inclusion. However, conventional wheelchairs often face significant limitations in narrow spaces and uneven terrains. The development of omnidirectional wheelchairs with suspension systems, as addressed in this work, is essential to tackle these challenges and offer greater independence to individuals with disabilities. These innovations can enhance quality of life by enabling access to previously inaccessible places and facilitating mobility in areas where, for example, sidewalks are deteriorated or nonexistent. The wheelchair was designed considering the challenges that conventional models face in terms of maneuverability and mobility in uneven terrains with small obstacles. The design process is briefly described, with a special focus on system requirements, conceptual design, hardware architecture, and the overall proposed design, along with the proposed control strategy. An analysis of the Mecanum-wheeled locomotion system when one of the wheels encounters an obstacle is also presented. It was concluded that the proposed design met the initial requirements, and that the suspension system allowed the wheelchair to navigate uneven terrains without experiencing significant changes in pitch or roll angles while keeping all four wheels in contact with the ground. Full article

The Mecanum-wheeled robot has four special wheels. It can control four wheels independently and has seven turning axes. The robot can translate in all directions and travel in curves without changing its direction by means of the control commands for turning ratio, speed, and direction of travel. However, no model has been proposed that can accurately simulate the output of the actual machine for the three types of inputs, even when the characteristics of the motor and motor driver are unknown. In this study, we synthesized and simplified transfer functions and estimated the undetermined coefficients that minimize the sum of squared errors to construct a model of the robot that can output the position and posture equivalent to those of the actual robot for the input commands for turning ratio, speed, and the direction of travel. We modeled a Mecanum-wheeled robot using the proposed modeling method and parameter determination method and compared the outputs of the real robot to the step and ramp inputs. The results showed that the errors between the two outputs were very small and accurate enough to simulate AI learning, such as reinforcement learning, using the model of the robot. Full article

This study proposes a nonlinear adaptive optimal control method, the adaptive H₂ control method, applied to the trajectory tracking problem of the wheeled mobile robot (WMR) with four-wheel mecanum wheels. From the perspective of solving mathematical problems, finding an analytical adaptive control solution that satisfies the adaptive H₂ performance criterion for the trajectory tracking problem of the WMR with four-wheel mecanum wheels is an extremely challenging task due to the high complexity of the dynamic system. To analytically derive the control law and adaptive control law for this trajectory tracking problem, a proportional-derivative (PD) type transformation is employed to formalize the trajectory tracking error dynamics between the WMR and the desired trajectory (DT). Based on an in-depth analysis of the trajectory tracking error dynamics, a closed-form adaptive control law is analytically derived from the highly complex nonlinear dynamic system equations. This control law provides a solution to the trajectory tracking problem of the WMR while satisfying the adaptive H₂ performance criterion. The proposed adaptive nonlinear control method offers a simple control structure and advantages such as improved energy efficiency. Finally, simulations and experimental implementations were conducted to verify the performance of the proposed adaptive H₂ control method and the H₂ control method in tracking the DT. The results demonstrate that, compared to the H₂ control method, the adaptive H₂ control method exhibits superior trajectory tracking performance, particularly in the presence of significant model uncertainties. Full article

This paper presents the trajectory tracking control design and implementation of feedback linearization (FL) and robust feedback linearization (RFL), applicable to a robotic lawnmower with four mecanum driving wheels. The RFL control design additionally includes a robust control law. These two nonlinear control laws are developed to enable the controlled robotic lawnmower to accurately follow any specified trajectory. The simulation outcomes illustrate that the suggested control law based on RFL displays superior trajectory tracking accuracy and resilience compared to the FL control method in the case of a robotic lawnmower operating under demanding conditions. These conditions encompass environmental disturbances and uncertainties in modeling. The RFL control method also exhibits lower energy consumption compared to the FL control method. Finally, using the RFL controller derived from this study, the error in trajectory tracking in computer simulations and the actual mowing performance have demonstrated outstanding results. Full article

This article investigates the limitations associated with traditional wheel-type pipeline walking devices, which are characterized by a single movement mode and an inability to navigate complex or irregular pipeline structures. A modular walking device (MWD) designed for pipeline robots was developed utilizing structural and mechanical analysis techniques. The reliability of the mechanical analysis was validated through single-factor dynamic testing. To analyze and optimize the factors influencing the maneuverability and obstacle-crossing capabilities of the MWD, a three-factor, three-level orthogonal testing method was utilized. The factors examined included the rotational speed of the walking wheel (RS), the pre-tightening force of the wheel brackets (PF), and the height of the annular obstacle (OH). The evaluation metrics used were the slip rate and passability. The results indicated that a parameter combination of RS at 70 rpm, PF at 30 N, and OH at 10 mm produced a slip rate of 11.6% ± 1.5%. During the obstacle traversal process, the remainder of the device maintained a safe distance from the obstacles, with only the walking wheel making contact. The verification testing also confirmed that the MWD is capable of executing three distinct modes of motion: rectilinear, rotational, and helical. The MWD designed and developed in this study can switch between multiple motion modes and successfully overcome obstacles within 15 mm, providing a new equipment for universities to enhance mechanized pipeline detection technology. Full article

This paper presents a mobile robot concept. To understand what has led to the choice of this particular design, one must first understand mobile robots in general: what are the trends, where are they used, etc. Then, some of the necessary elements for robot propulsion and navigation were considered, looking at their principle of operation, as well as their application. A description of the robot structure follows. Thanks to the software, the approximate value of the various parameters can be calculated, and an initial three-dimensional model can be built. First, the idea of the robot will be introduced in the abstract and then be outlined in detail, showing how the various components work. It will conclude by looking at the most important elements of a mobile robot, as well as what makes a robot successful. Full article

In adapting to the demands of this modernized landscape, a conventional human-operated forklift within an industrial or warehouse setting falls short. However, the adoption of autonomous forklifts remains a distant prospect for many companies, primarily due to the formidable implementation and switching costs associated with artificial intelligence and complex control mechanisms. To bridge this gap, we present the development of a teleoperated forklift utilizing mecanum wheels for enhanced maneuverability. A key contribution of this work lies in the design of a novel synchronization method for the precise position control of the pallet carriers. This method surpasses the conventional independent and master–slave approaches, demonstrably achieving superior tracking and synchronization performance. Also, a model-based velocity control algorithm was designed for the mecanum wheels to facilitate the mobility of the system. The forklift was successfully able to carry a maximum load of 300 kg. For the comparison of the tracking and synchronization performance, the independent and master–slave methods were also applied to the system. The proposed method showed better performance compared to other structures. Full article

This scientific paper presents the development and validation process of a dynamic model in Simulink used for decision-making regarding the locomotion and driving type of autonomous omnidirectional mobile platforms. Unlike traditional approaches relying on differential equations, this study uses Simulink’s block-based diagrams, offering a simpler and efficient development process. Importantly, the dynamic model accounts for friction forces, a critical factor for energy monitoring. The model’s validation is conducted experimentally, ensuring its accuracy and reliability. This paper formulates mathematical models for both conventional and Mecanum wheel configurations, facilitating energy-efficient driving strategies. By decomposing resistive forces into inertial and frictional components using the Jacobian matrix, this study accurately simulates electrical current consumption during robot motion. Through fuzzy decision algorithms utilizing parameters such as energy consumption, travel time, precision, and desired maneuverability, this paper proposes a method for determining the optimal locomotion mode for mobile platforms with Mecanum wheels. Overall, this research brings a new contribution to the field of mobile robotics by providing a comprehensive framework for dynamic modeling and it offers the possibility to drive omnidirectional robots in an energy-efficient manner. Full article

The rise of smart factories and warehouses has ushered in an era of intelligent manufacturing, with autonomous robots playing a pivotal role. This study focuses on improving the navigation and control of autonomous forklifts in warehouse environments. It introduces an innovative approach that combines a modified Linear Segment with Parabolic Blends (LSPB) trajectory planning with Model Predictive Control (MPC) to ensure efficient and secure robot movement. To validate the performance of our proposed path-planning method, MATLAB-based simulations were conducted in various scenarios, including rectangular and warehouse-like environments, to demonstrate the feasibility and effectiveness of the proposed method. The results demonstrated the feasibility of employing Mecanum wheel-based robots in automated warehouses. Also, to show the superiority of the proposed control algorithm performance, the navigation results were compared with the performance of a system using the PID control as a lower-level controller. By offering an optimized path-planning approach, our study enhances the operational efficiency and effectiveness of Mecanum wheel robots in real-world applications such as automated warehousing systems. Full article

This paper introduces the mechanical design and control system of a mobile robot for logistics transportation in manufacturing workshops. The robot is divided into a moving part and a grasping part. The moving part adopts the mecanum wheel four-wheel-drive chassis, which has omnidirectional moving ability. The mechanical system is based on four mechanical wheels, and a modular suspension mechanism is designed. The grasping part is composed of a depth camera, a cooperative manipulator, and an electric claw. Finally, the two are coordinated and controlled by computer. The controller hardware of the mobile platform is designed, and the functional modules of the mobile platform are designed based on the RT thread embedded system. For the navigation part of the mobile robot, a fuzzy PID deviation correction algorithm is designed and simulated. Using the Hough circular transform algorithm, the visual grasping of the manipulator is realized. Finally, the control mode of the computer-controlled manipulator and the manipulator-controlling mobile platform is adopted to realize the feeding function of the mobile robot, and the experimental verification is carried out. Full article