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

Control of Multiple Arm Systems With Rolling Constraints

When multiple arms are used to manipulate a large object, it is necessary to maintain and control contacts between the object and effector(s) on one or more arms. The contacts are characterized by holonomic as well as nonholonomic constraints. This paper addresses the control of mechanical systems subject to nonholonomic constraints, rolling constraints in particular. It has been shown that such a system is always controllable, but cannot be stabilized to a single equilibrium by smooth feedback [l, 2]. In this paper, we show that the system is not input-state linearizable though input-output linearization is possible with appropriate output equations. Further, if the system is position-controlled (i.e., the output equation is a functions of position variables only), it has a zero dynamics which is Lagrange stable but not asymptotically stable. We discuss the analysis and controller design for planar as well as spatial multi-arm systems and present results from computer simulations to demonstrate the theoretical results

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

Modeling, Analysis, and Control of a Mobile Robot for \u3ci\u3eIn Vivo\u3c/i\u3e Fluoroscopy of Human Joints during Natural Movements

In this dissertation, the modeling, analysis and control of a multi-degree of freedom (mdof) robotic fluoroscope was investigated. A prototype robotic fluoroscope exists, and consists of a 3 dof mobile platform with two 2 dof Cartesian manipulators mounted symmetrically on opposite sides of the platform. One Cartesian manipulator positions the x-ray generator and the other Cartesian manipulator positions the x-ray imaging device. The robotic fluoroscope is used to x-ray skeletal joints of interest of human subjects performing natural movement activities. In order to collect the data, the Cartesian manipulators must keep the x-ray generation and imaging devices accurately aligned while dynamically tracking the desired skeletal joint of interest. In addition to the joint tracking, this also requires the robotic platform to move along with the subject, allowing the manipulators to operate within their ranges of motion. A comprehensive dynamic model of the robotic fluoroscope prototype was created, incorporating the dynamic coupling of the system. Empirical data collected from an RGB-D camera were used to create a human kinematic model that can be used to simulate the joint of interest target dynamics. This model was incorporated into a computer simulation that was validated by comparing the simulation results with actual prototype experiments using the same human kinematic model inputs. The computer simulation was used in a comprehensive dynamic analysis of the prototype and in the development and evaluation of sensing, control, and signal processing approaches that optimize the subject and joint tracking performance characteristics. The modeling and simulation results were used to develop real-time control strategies, including decoupling techniques that reduce tracking error on the prototype. For a normal walking activity, the joint tracking error was less than 20 mm, and the subject tracking error was less than 140 mm

Robust model predictive kinematic tracking control with terminal region for wheeled robotic systems

This paper addresses the nonlinear model predictive control (MPC) for wheeled mobile robots (WMRs) under external disturbance. The decoupling technique is utilized based on the non-holonomic constraint description for separating the WMR model. This method is able to achieve the under-actuated kinematic sub-system without disturbance and fully-actuated dynamic sub-system in presence of disturbance. Thanks to the decoupling technique, the disturbance is lumped into dynamic sub-system. The novelty lies in that the MPC-based tracking control with fixed initial point guarantees the stability based on a new establishment of terminal region and equivalent terminal controller. The feasibility problem is demonstrated to lead the tracking problem using theoretical analysis. Moreover, the control structure is inserted more the robust nonlinear dynamic controller. The effectiveness and advantages of the proposed control scheme are verified by numerical simulations using Yamip tool

Research on a semiautonomous mobile robot for loosely structured environments focused on transporting mail trolleys

In this thesis is presented a novel approach to model, control, and planning the motion of a nonholonomic wheeled mobile robot that applies stable pushes and pulls to a nonholonomic cart (York mail trolley) in a loosely structured environment. The method is based on grasping and ungrasping the nonholonomic cart, as a result, the robot changes its kinematics properties. In consequence, two robot configurations are produced by the task of grasping and ungrasping the load, they are: the single-robot configuration and the robot-trolley configuration. Furthermore, in order to comply with the general planar motion law of rigid bodies and the kinematic constraints imposed by the robot wheels for each configuration, the robot has been provided with two motorized steerable wheels in order to have a flexible platform able to adapt to these restrictions. [Continues.

Control of Mechanical Systems With Rolling Constraints: Application to Dynamic Control of Mobile Robots

There are many examples of mechanical systems which require rolling contacts between two or more rigid bodies. Rolling contacts engender nonholonomic constraints in an otherwise holonomic system. In this paper, we develop a unified approach to the control of mechanical systems subject to both holonomic and nonholonomic constraints. We first present a state space realization of a constrained system and show that it is not input-state linearizable. We then discuss the input-output linearization and zero dynamics of the system. This approach is applied to the dynamic control of mobile robots. Two types of control algorithms for mobile robots are investigated: (a) trajectory tracking, and (b) path following. In each case, a smooth nonlinear feedback is obtained to achieve asymptotical input-output stability, and Lagrange stability of the overall system. Simulation results are presented to demonstrate the effectiveness of the control algorithms and to compare the performance of trajectory tracking and path following algorithms

Adaptive Path Following for an Underactuated Nonholonomic Mobile Manipulator

We investigate an adaptive path following problem for an underactuated nonholonomic mobile manipulator system and closed planar curves. As opposed to adapting to uncertain or unknown dynamics in the plant, we apply an adaptation approach with respect to an unknown geometric path. First, we present a solution to the non-adaptive path following problem using the concept of a path following output and apply it to circular and elliptical paths. To overcome a drawback associated with our first proposed solution and set the stage for our approach to the adaptive case, we apply an approximation approach based on osculating circles for strictly convex closed curves. We transition to the adaptive path following case by first presenting an algorithm to estimate unknown path parameters in the case of a circular path. We use our estimation algorithm and our path following solution for circular paths in an indirect adaptive control scheme. Thereafter, again using the osculating circle of a curve and the approximation technique of our second non-adaptive path following solution, we extend our adaptive solution, under some mild assumptions, for unknown strictly convex closed curves in the plane

Recent Advances in Robust Control

Robust control has been a topic of active research in the last three decades culminating in H_2/H_\infty and \mu design methods followed by research on parametric robustness, initially motivated by Kharitonov's theorem, the extension to non-linear time delay systems, and other more recent methods. The two volumes of Recent Advances in Robust Control give a selective overview of recent theoretical developments and present selected application examples. The volumes comprise 39 contributions covering various theoretical aspects as well as different application areas. The first volume covers selected problems in the theory of robust control and its application to robotic and electromechanical systems. The second volume is dedicated to special topics in robust control and problem specific solutions. Recent Advances in Robust Control will be a valuable reference for those interested in the recent theoretical advances and for researchers working in the broad field of robotics and mechatronics