Search Results (8)

In this work, we present an analysis of, as well as driving strategies and design considerations for, a type of omnidirectional mobile robot: the offset-differential robot. This system presents omnidirectionality while using any type of standard wheel, allowing for applications in uneven and rough terrains, as well as cluttered environments. The known fact that these robots, as well as simple differential robots, have an unstable driving zone, has mostly been dealt with by designing driving strategies in the stable zone of internal dynamics. However, driving in the unstable zone may be advantageous when dealing with rough and uneven terrains. This work is based on the full kinematic and dynamic analysis of a robot, including its passive elements, to explain the unexpected behaviors that appear during its motion due to instability. Precise torque calculations taking into account the configuration of the passive elements were performed for better torque control, and design recommendations are included. The stable and unstable behaviors were characterized, and driving strategies were described in order to achieve the desired performance regarding precise positioning and speed. The model and driving strategies were validated through simulations and experimental testing. This work lays the foundation for the design of better control strategies for offset-differential robots. Full article

This paper proposes a new trajectory tracking control scheme for the four mecanums wheel omnidirectional mobile robot (FM-OMR). Considering the influence of uncertainty on tracking accuracy, a self-organizing fuzzy neural network approximator (SOT1FNNA) is proposed to estimate the uncertainty. In particular, since the structure of traditional approximation network is preset, it will cause problems such as input constraints and rule redundancy, resulting in low adaptability of the controller. Therefore, a self-organizing algorithm including rule growth and local access is designed according to the tracking control requirements of omnidirectional mobile robots. In addition, a preview strategy (PS) based on Bezier curve trajectory re-planning is proposed to solve the problem of tracking curve instability caused by the lag of tracking starting point. Finally, the simulation verifies the effectiveness of this method in tracking and trajectory starting point optimization. Full article

In this paper, a fuzzy neural network based predefined-time trajectory tracking control method is proposed for the tracking problem of omnidirectional mobile robots (FM-OMR) with uncertainties. Considering the requirement of tracking error convergence time, a position tracking controller based on predefined-time stability is proposed. Compared with the traditional position tracking control method, the minimum upper bound of the convergence time can be explicitly set. In order to obtain more accurate angular velocity tracking, the inner loop controller combines Type 1 fuzzy neural network (T1FNN) to estimate the uncertainty. In addition, considering the problem of feedback channel noise, a Kalman filter combining velocity and position information is proposed. Finally, the simulation results verify the effectiveness of this method. Full article

Monitoring and tracking issues related to autonomous mobile robots are currently intensively debated in order to ensure a more fluent functionality in supply chain management. The interest arises from both theoretical and practical concerns about providing accurate information about the current and past position of systems involved in the logistics chain, based on specialized sensors and Global Positioning System (GPS). The localization demands are more challenging as the need to monitor the autonomous robot’s ongoing activities is more stringent indoors and benefit from accurate motion response, which requires calibration. This practical research study proposes an extended calibration approach for improving Omnidirectional Mobile Robot (OMR) motion response in the context of mechanical build imperfections (misalignment). A precise indoor positioning system is required to obtain accurate data for calculating the calibration parameters and validating the implementation response. An ultrasound-based commercial solution was considered for tracking the OMR, but the practical observed errors of the readily available position solutions requires special processing of the raw acquired measurements. The approach uses a multilateration technique based on the point-to-point distances measured between the mobile ultrasound beacon and a current subset of fixed (reference) beacons, in order to obtain an improved position estimation characterized by a confidence coefficient. Therefore, the proposed method managed to reduce the motion error by up to seven-times. Reference trajectories were generated, and robot motion response accuracy was evaluated using a Robot Operating System (ROS) node developed in Matlab-Simulink that was wireless interconnected with the other ROS nodes hosted on the robot navigation controller. Full article

With the expansion of the cyber-physical system (CPS) application area, its importance has become more and more prominent. As one of the typical applications of CPS, the anomaly detections of mobile robots have attracted the attention of all parties. As part of the CPS, mobile robots face the problem that conventional residual-based detection methods cannot identify stealthy anomalies. The conventional residual-based detection methods mainly use the residual signal calculated from the control signal and measure output for detection, which is widely used in fault diagnosis. Still, it is difficult to be useful in deceptive stealthy anomalies purposefully imposed on mobile robots, which are designed to evade the conventional detections by tampering with measure output. Furthermore, they can control the system to deviate from the expected operations, causing degradation of control performance or even damage without being detected. Based on this, by analyzing the system model of CPS and the stealthy conditions of anomalies, the improved residual-based detection method is proposed in this paper. Moreover, three stealthy anomalies purposefully imposed on an omnidirectional mobile robot (OMR) are detected by using the conventional residual-based methods and the improved residual-based method. Finally, the experimental results show that the method proposed can effectively detect the stealthy anomalies purposefully imposed on the OMR. Full article

Motion control in dynamic environments is one of the most important problems in using mobile robots in collaboration with humans and other robots. In this paper, the motion control of a four-Mecanum-wheeled omnidirectional mobile robot (OMR) in dynamic environments is studied. The robot’s differential equations of motion are extracted using Kane’s method and converted to discrete state space form. A nonlinear model predictive control (NMPC) strategy is designed based on the derived mathematical model to stabilize the robot in desired positions and orientations. As a main contribution of this work, the velocity obstacles (VO) approach is reformulated to be introduced in the NMPC system to avoid the robot from collision with moving and fixed obstacles online. Considering the robot’s physical restrictions, the parameters and functions used in the designed control system and collision avoidance strategy are determined through stability and performance analysis and some criteria are established for calculating the best values of these parameters. The effectiveness of the proposed controller and collision avoidance strategy is evaluated through a series of computer simulations. The simulation results show that the proposed strategy is efficient in stabilizing the robot in the desired configuration and in avoiding collision with obstacles, even in narrow spaces and with complicated arrangements of obstacles. Full article

A mobile robot with no less than two powered caster wheels (PCWs) has the ability to perform omnidirectional motions and belongs to a redundantly actuated system. Redundant actuation will bring the issue of non-uniqueness of actuating torque distribution, and inappropriate choices of torque distribution schemes will lead to unexpected large required actuating torques and extra energy consumption. This paper proposes a new torque distribution optimization approach based on a gradient projection method (GPM) for the omnidirectional mobile robot (OMR) with direct drive PCWs. It can significantly reduce the maximal required actuating torque and the energy consumption of the system. The modular kinematic and dynamic modeling method is presented first, which is suitable for an arbitrary number of employed PCWs, as well as their install positions in the chassis. The detailed energy consumption model of the OMR, including output energy consumption and electrical energy loss, is formulated through experimental testing. The effectiveness of the proposed algorithms is validated by simulation examples. Lastly, the computational efficiency of the method is verified. Full article

This paper addresses trajectory tracking of an omni-directional mobile robot (OMR) with three mecanum wheels and a fully symmetrical configuration. The omni-directional wheeled robot outperforms the non-holonomic wheeled robot due to its ability to rotate and translate independently and simultaneously. A kinematics model of the OMR is established and a model predictive control (MPC) algorithm with control and system constraints is designed to achieve point stabilization and trajectory tracking. Simulation results validate the accuracy of the established kinematics model and the effectiveness of the proposed MPC controller. Full article