Dynamic modeling and tracking control of a nonholonomic wheeled mobile manipulator with dual arms

This paper presents methodologies for dynamic modeling and trajectory tracking of a nonholonomic wheeled mobile manipulator (WMM) with dual arms. The complete dynamic model of such a manipulator is easily established using the Lagrange's equation and MATHEMATICA. The structural properties of the overall system along with its subsystems are also well investigated and then exploited in further controller synthesis. The derived model is shown valid by reducing it to agree well with the mobile platform model. In order to solve the path tracking control problem of the wheeled mobile manipulator, a novel kinematic control scheme is proposed to deal with the nonholonomic constraints. With the backstepping technique and the filtered-error method, the nonlinear tracking control laws for the mobile manipulator system are constructed based on the Lyapunov stability theory. The proposed control scheme not only achieves simultaneous trajectory and velocity tracking, but also compensates for the dynamic interactions caused by the motions of the mobile platform and the two onboard manipulators. Simulation results are performed to illustrate the efficacy of the proposed control strategy

Mobile parallel manipulator consisting of two nonholonomic carts and their path planning

Mobile manipulators are widely used to transport and manipulate objects in industrial settings. In this paper, we propose a mobile manipulator that consists of a parallel mechanism and two two-wheel-drive carts. The planar motions of the carts are transmitted to a platform through three screw pairs of the parallel mechanism, allowing the pose of the platform to be controlled by only four motors. Kinematic analysis for such a two-cart mobile manipulator gives a Jacobian matrix, reveals the effects of nonholonomic constraints, and demonstrates that the yaw angle of the platform must be limited to avoid singular and failure configurations, and that the pitch angle is quite sensitive to uncertainties. Based on these analysis results, we present a custom path planning method for the carts. This method provides a non-optimal but easily realizable path planning algorithm with low computational cost, since the complex constraint conditions of this two-cart mobile manipulator have little influence on the proposed path generation process. The path planning process consists of four steps. We describe the motions of the carts in each step and establish a path tracking control system for the carts. Some simulations are conducted to show the motions of the carts, investigate the changes in the pose of the platform, and quantitatively evaluate the sensitivity of the platform’s pitch angle. Moreover, we construct an experimental prototype and conduct experiments to verify the validity and usefulness of the proposed mechanism and path planning method

Coordinated Control of a Mobile Manipulator

In this technical report, we investigate modeling, control, and coordination of mobile manipulators. A mobile manipulator in this study consists of a robotic manipulator and a mobile platform, with the manipulator being mounted atop the mobile platform. A mobile manipulator combines the dextrous manipulation capability offered by fixed-base manipulators and the mobility offered by mobile platforms. While mobile manipulators offer a tremendous potential for flexible material handling and other tasks, at the same time they bring about a number of challenging issues rather than simply increasing the structural complexity. First, combining a manipulator and a platform creates redundancy. Second, a wheeled mobile platform is subject to nonholonomic constraints. Third, there exists dynamic interaction between the manipulator and the mobile platform. Fourth, manipulators and mobile platforms have different bandwidths. Mobile platforms typically have slower dynamic response than manipulators. The objective of the thesis is to develop control algorithms that effectively coordinate manipulation and mobility of mobile manipulators. We begin with deriving the motion equations of mobile manipulators. The derivation presented here makes use of the existing motion equations of manipulators and mobile platforms, and simply introduces the velocity and acceleration dependent terms that account for the dynamic interaction between manipulators and mobile platforms. Since nonholonomic constraints play a critical role in control of mobile manipulators, we then study the control properties of nonholonomic dynamic systems, including feedback linearization and internal dynamics. Based on the newly proposed concept of preferred operating region, we develop a set of coordination algorithms for mobile manipulators. While the manipulator performs manipulation tasks, the mobile platform is controlled to always bring the configuration of the manipulator into a preferred operating region. The control algorithms for two types of tasks - dragging motion and following motion - are discussed in detail. The effects of dynamic interaction are also investigated. To verify the efficacy of the coordination algorithms, we conduct numerical simulations with representative task trajectories. Additionally, the control algorithms for the dragging motion and following motion have been implemented on an experimental mobile manipulator. The results from the simulation and experiment are presented to support the proposed control algorithms

Passivity-Based Tracking Control of a Mobile Manipulator Robot

This work presents a control approach based on the passivity principle, developed to guarantee performance of the application used to track the trajectory of mobile manipulator when disturbed. By exploiting the particularity of the mobile manipulator robots modelling equipped with a nonholonomic mobile base, we present a global control law for the mobile manipulator as a single system. This control allows taking into account the whole system and modifying its dynamics by introducing a highly non-linear regressor matrix to consider uncertainties and modeling constraints. The presented controller is applied to the mobile manipulator robot composed of a manipulator's arm with 2 DDL mounted on a mobile unicycle platform. Simulation tests validate the performance of the proposed approach when external disturbances occur; showing an acceptable performance of the system's stability and validated by exploiting the Lyapunov theory. &nbsp

Passivity-Based Tracking Control of a Mobile Manipulator Robot

This work presents a control approach based on the passivity principle, developed to guarantee performance of the application used to track the trajectory of mobile manipulator when disturbed. By exploiting the particularity of the mobile manipulator robots modelling equipped with a nonholonomic mobile base, we present a global control law for the mobile manipulator as a single system. This control allows taking into account the whole system and modifying its dynamics by introducing a highly non-linear regressor matrix to consider uncertainties and modeling constraints. The presented controller is applied to the mobile manipulator robot composed of a manipulator's arm with 2 DDL mounted on a mobile unicycle platform. Simulation tests validate the performance of the proposed approach when external disturbances occur; showing an acceptable performance of the system's stability and validated by exploiting the Lyapunov theory. &nbsp

Coordinating Locomotion and Manipulation of a Mobile Manipulator

A mobile manipulator in this study is a manipulator mounted on a mobile platform. Assuming the end point of the manipulator is guided, e.g., by a human operator to follow an arbitrary trajectory, it is desirable that the mobile platform is able to move as to position the manipulator in certain preferred configurations. Since the motion of the manipulator is unknown a priori, the platform has to use the measured joint position information of the manipulator for motion planning. This paper presents a planning and control algorithm for the platform so that the manipulator is always positioned at the preferred configurations measured by its manipulability. Simulation results are presented to illustrate the efficacy of the algorithm. The use of the resulting algorithm in a number of applications is also discussed

Intelligent Adaptive Motion Control for Ground Wheeled Vehicles

In this paper a new intelligent adaptive control is applied to solve a problem of motion control of ground vehicles with two independent wheels actuated by a differential drive. The major objective of this work is to obtain a motion control system by using a new fuzzy inference mechanism where the Lyapunov’s stability can be assured. In particular the parameters of the kinematical control law are obtained using an intelligent Fuzzy mechanism, where the properties of the Fuzzy maps have been established to have the stability above. Due to the nonlinear map of the intelligent fuzzy inference mechanism (i.e. fuzzy rules and value of the rule), the parameters above are not constant, but, time after time, based on empirical fuzzy rules, they are updated in function of the values of the tracking errors. Since the fuzzy maps are adjusted based on the control performances, the parameters updating assures a robustness and fast convergence of the tracking errors. Also, since the vehicle dynamics and kinematics can be completely unknown, a dynamical and kinematical adaptive control is added. The proposed fuzzy controller has been implemented for a real nonholonomic electrical vehicle. Therefore system robustness and stability performance are verified through simulations and experimental studies

Mobile camera-space manipulation

The invention is a method of using computer vision to control systems consisting of a combination of holonomic and nonholonomic degrees of freedom such as a wheeled rover equipped with a robotic arm, a forklift, and earth-moving equipment such as a backhoe or a front-loader. Using vision sensors mounted on the mobile system and the manipulator, the system establishes a relationship between the internal joint configuration of the holonomic degrees of freedom of the manipulator and the appearance of features on the manipulator in the reference frames of the vision sensors. Then, the system, perhaps with the assistance of an operator, identifies the locations of the target object in the reference frames of the vision sensors. Using this target information, along with the relationship described above, the system determines a suitable trajectory for the nonholonomic degrees of freedom of the base to follow towards the target object. The system also determines a suitable pose or series of poses for the holonomic degrees of freedom of the manipulator. With additional visual samples, the system automatically updates the trajectory and final pose of the manipulator so as to allow for greater precision in the overall final position of the system