Motion coordination and reactive control of autonomous multi-manipulator systems

The emerging field of service robots demands new systems with increased flexibility. The flexibility of a robot system can be increased in many different ways. Mobile manipulation—the coordinated use of manipulation capabilities and mobility—is an approach to increase robots flexibility with regard to their motion capabilities. Most mobile manipulators that are currently under development use a single arm on a mobile platform. The use of a two-arm manipulator system allows increased manipulation capabilities, especially when large, heavy, or non-rigid objects must be manipulated. This article is concerned with motion control for mobile two-arm systems. These systems require new schemes for motion coordination and control. A coordination scheme called transparent coordination is presented that allows for an arbitrary number of manipulators on a mobile platform. Furthermore, a reactive control scheme is proposed to enable the platform to support sensor-guided manipulator motion. Finally, this article introduces a collision avoidance scheme for mobile two-arm robots. This scheme surveys the vehicle motion to avoid platform collisions and arm collisions caused by self-motion of the robot. © 1996 John Wiley & Sons, Inc.     

Analysis and experiments with an elephant's trunk robot

The area of trunk/tentacle-type biological manipulation is not new, but there has been little progress in the development and application of a physical device to simulate these types of manipulation. Our research in this area is based on using an 'elephant trunk' robot. In this paper, we review the construction of the robot and how it compares to biological manipulators. We apply our previously designed kinematic model to describe the kinematics of the robot. We finish by providing some examples of motion planning and intelligent manipulation using the robot.     

Analysis and experiments with an elephant's trunk robot.

The area of tentacle and trunk type biological manipulation is not new, but there has been little progress in the development and application of a physical device to simulate these types of manipulation. Our research in this area is based on using an 'elephant trunk' robot. In this paper, we review the construction of the robot and how it compares to biological manipulators. We then apply our previously designed kinematic model to describe the kinematics of the robot. We finish by providing some examples of motion planning and intelligent manipulation using the robot.     

多机器人协同吊运系统的协调动态载荷分配

针对多机器人共同吊运同一个物体形成闭运动链的协调系统,利用用牛顿-欧拉法建立了系统的广义动力学方程.研究了多机器人协调吊运系统动态载荷的一种实时性分配方法.根据各机器人的承载力,用线性加权方法使被吊运物质心处的内力有限并获得了系统的载荷分配原则.随后根据被吊运物的期望运动,给出了系统动态载荷分配的解析表达式,并进而可计算得到各机器人的期望工作载荷.最后,采用ABB工业机器人搭建吊运平台,实验验证所获得的载荷分配方法.研究结果为进一步研究多移动机器人协调吊运系统的载荷分配问题打下基础.     

Redundancy modelling and resolution for robotic mobile manipulators: a general approach

In this work the topic of kinematic redundancy modelling and resolution for robotic mobile manipulators is considered. A set of redundancy parameters is introduced to define a general inverse kinematic procedure for mobile manipulators. Then, redundancy is treated as a non-linear optimization problem with the purpose of finding robot configurations that maximize the designed metric measures. Some strategies to design the optimization objective function are introduced in order to achieve desirable redundant behaviours, such as obstacles avoidance, mobile base motions reductions and dexterity optimization. Moreover, the robot controller has been developed following an object-oriented software architecture principle that allows to keep it general and robot independent. As a prove of reliability and generality of our approach, the same controller has been used to control several different mobile manipulators in a simulation environment, as well as a real KUKA youBot robot.     

Two fault detection and isolation schemes for robot manipulators using soft computing techniques

With growing technology, fault detection and isolation (FDI) have become one of the interesting and important research areas in modern control and signal processing. Accomplishment of specific missions like waste treatment in nuclear reactors or data collection in space and underwater missions make reliability more important for robotics and this demand forces researchers to adapt available FDI studies on nonlinear systems to robot manipulators, mobile robots and mobile manipulators.In this study, two model-based FDI schemes for robot manipulators using soft computing techniques, as an integrator of Neural Network (NN) and Fuzzy Logic (FL), are proposed. Both schemes use M-ANFIS for robot modelling. The first scheme isolates faults by passing residual signals through a neural network. The second scheme isolates faults by modelling faulty robot models for defined faults and combining these models as a generalized observers scheme (GOS) structure. Performances of these schemes are tested on a simulated two-link planar manipulator and simulation results and a comparison according to some important FDI specifications are presented.     

Planning of collision-free paths for a reconfigurable dual manipulator equipped mobile robot

In this paper, we study the problem of finding a collision-free path for a mobile robot which possesses manipulators. The task of the robot is to carry a polygonal object from a starting point to a destination point in a possibly culttered environment. In most of the existing research on robot path planning, a mobile robot is approximated by a fixed shape, i.e., a circle or a polygon. In our task planner, the robot is allowed to change configurations for avoiding collision. This path planner operates using two algorithms: the collision-free feasible configuration finding algorithm and the collision-free path finding algorithm. The collision-free feasible configuration finding algorithm finds all collision-free feasible configurations for the robot when the position of the carried object is given. The collision-free path finding algorithm generates some candidate paths first and then uses a graph search method to find a collision-free path from all the collision-free feasible configurations along the candidate paths. The proposed algorithms can deal with a cluttered environment and is guaranteed to find a solution if one exists.     

A Neural Network Controller for Continuum Robots

Continuum or hyper-redundant robot manipulators can exhibit behavior similar to biological trunks, tentacles, or snakes. Unlike traditional rigid-link robot manipulators, continuum robot manipulators do not have rigid joints, hence these manipulators are extremely dexterous, compliant, and are capable of dynamic adaptive manipulation in unstructured environments. However, the development of high-performance control algorithms for these manipulators is quite a challenge, due to their unique design and the high degree of uncertainty in their dynamic models. In this paper, a controller for continuum robots, which utilizes a neural network feedforward component to compensate for dynamic uncertainties is presented. Experimental results using the OCTARM, which is a soft extensible continuum manipulator, are provided to illustrate that the addition of the neural network feedforward component to the controller provides improved performance.     

Combinatorial Optimization and Performance Analysis of a Multi-arm Cartesian Robotic Fruit Harvester—Extensions of Graph Coloring

A mobile melon robotic harvester consisting of multiple Cartesian manipulators, each with three degrees of freedom, is being developed. In order to design an optimal robot in terms of number of arms, manipulator capabilities, and robot speed, a method of allocating the fruits to be picked by each manipulator in a way that yields the maximum harvest has been developed. Such a method has already been devised for a multi-arm robot with 2DOF each. The maximum robotic harvesting problem was shown there to be an example of the maximum k-colorable subgraph problem (MKCSP) on an interval graph. However, for manipulators with 3DOF, the additional longitudinal motion results in variable intervals. To overcome this issue, we devise a new model based on the color-dependent interval graph (CDIG). This enables the harvest by multiple robotic arms to be modeled as a modified version of the MKCSP. Based on previous research, we develop a greedy algorithm that solves the problem in polynomial time, and prove its optimality using induction. As with the multi-arm 2DOF robot, when simulated numerous times on a field of randomly distributed fruits, the algorithm yields a nearly identical percentage of fruit harvested for given robot parameters. The results of the probabilistic analysis developed for the 2DOF robot was modified to yield a formula for the expected harvest ratio of the 3DOF robot. The significance of this method is that it enables selecting the most efficient actuators, number of manipulators, and robot forward velocity for maximal robotic fruit harvest.     

Effect of Terrain Traction,Suspension Stiffness and Grasp Posture on the Tip-Over Stability of Wheeled Robots with Multiple Arms

Abstract

In this paper, dynamics, postural stability and control of suspended wheeled mobile manipulators for cooperative heavy object manipulation are elaborated considering the effect of grasping posture. The presented model considers a system equipped with multiple manipulators with flexible suspension, which also contains an accurate nonlinear behavior of the tires. Moreover, it includes the vibratory response of the tires as unsprung masses. Therefore, this is one of the most complete models that have been presented for wheeled mobile manipulators to date. First, based on the Newton–Euler formulation for a chain of rigid bodies, the dynamics model of such complicated systems in three-dimensional maneuvers is developed without considering a nonlinear frictional model of tires, which was verified using the ADAMS multibody simulator. Then, a proper nonlinear friction model is added to the developed dynamics to provide a more complete one. Considering pneumatic tires, the Dugoff tire friction model is adopted to describe the longitudinal and lateral forces produced at the contact patch of the wheels. Using the obtained dynamics along with the moment-height stability measure the effect of frictional effects as well as suspension attributes on the postural stability of such systems are accurately investigated for maneuvers over flat and rough terrains. Finally, the effect of grasping posture and relevant configuration of the robot on the stability of the system is examined during a heavy object manipulation task.     

Markerless human–robot interface for dual robot manipulators using Kinect sensor

Remote teleoperation of robot manipulators is often necessary in unstructured, dynamic, and dangerous environments. However, the existing mechanical and other contacting interfaces require unnatural, or hinder natural, human motions. At present, the contacting interfaces used in teleoperation for multiple robot manipulators often require multiple operators. Previous vision-based approaches have only been used in the remote teleoperation for one robot manipulator as well as require the special quantity of illumination and visual angle that limit the field of application. This paper presents a noncontacting Kinect-based method that allows a human operator to communicate his motions to the dual robot manipulators by performing double hand–arm movements that would naturally carry out an object manipulation task. This paper also proposes an innovative algorithm of over damping to solve the problem of error extracting and dithering due to the noncontact measure. By making full use of the human hand–arm motion, the operator would feel immersive. This human–robot interface allows the flexible implementation of the object manipulation task done in collaboration by dual robots through the double hand–arm motion by one operator.     

The SDRE control of mobile base cooperative manipulators: Collision free path planning and moving obstacle avoidance

This work proposes application of a state-dependent Riccati equation (SDRE) controller for wheeled mobile cooperative manipulators. Implementation of the SDRE on a wheeled mobile manipulator (WMM) considering holonomic and non-holonomic constraints is difficult and leads to instability of the system. The present study introduces a method of controlling the WMMs including: a general formulation, state-dependent coefficient parameterization, and control structure of the SDRE. Overcoming the problem of instability of the WMM resulted in control design for a system of cooperative manipulators mounted on a wheeled mobile platform. Optimal load distribution (OLD) was employed to distribute the load between the cooperative arms. The presence of obstacles and the probability of a collision between multiple robots in a workspace are the motivations behind employment of the artificial potential field (APF) approach. Two cooperative manipulators mounted on a mobile platform retrieved from Scout robot were modeled and simulated for situations such as controlling multiple mobile bases (collision avoidance), a cooperative system of manipulators, and moving obstacle avoidance. The OLD improved the load capacity, precision, and stability in motion of the cooperative system. Compatibility of the APF within the structure of the SDRE controller is another promising aspect of this research.     

Adaptive neural controller for cooperative multiple robot manipulator system manipulating a single rigid object

In this article, an adaptive neural controller is developed for cooperative multiple robot manipulator system carrying and manipulating a common rigid object. In coordinated manipulation of a single object using multiple robot manipulators simultaneous control of the object motion and the internal force exerted by manipulators on the object is required. Firstly, an integrated dynamic model of the manipulators and the object is derived in terms of object position and orientation as the states of the derived model. Based on this model, a controller is proposed that achieves required trajectory tracking of the object as well as tracking of the desired internal forces arising in the system. A feedforward neural network is employed to learn the unknown dynamics of robot manipulators and the object. It is shown that the neural network can cope with the unknown nonlinearities through the adaptive learning process and requires no preliminary offline learning. The adaptive learning algorithm is derived from Lyapunov stability analysis so that both error convergence and tracking stability are guaranteed in the closed loop system. Finally, simulation studies and analysis are carried out for two three-link planar manipulators moving a circular disc on specified trajectory.     

Contact instability of the direct drive robot when constrained by arigid environment

A sufficient condition for the stability of robot manipulators in constrained maneuvers is derived. Attention is focused on the class of direct drive robots whose rigid links dominate the robot's dynamic behavior; compared to the robot, the environment is assumed to be infinitely rigid. The stability of the manipulator-environment system is investigated, and a bound for stable manipulation is determined. This bound is verified via simulation and experiment on the Minnesota direct drive robot     

A HUMANLIKE GRASPING FORCE PLANNER FOR OBJECT MANIPULATION BY ROBOT MANIPULATORS

Recently robot manipulators have been expected to perform sophisticated tasks such as object manipulation, assembly tasks, or cooperative tasks with human workers. In order to realize these tasks with robot manipulators, it is important to understand the human strategy of object grasping and manipulation. In this study, we have examined how a human being decides the grasping force necessary to manipulate an unknown object in order to apply human object-grasping strategy for robotic systems. Experiments have been performed with several kinds of objects under several kinds of conditions to investigate how much grasping force human subjects generate. Adjustment strategy of human grasping force when the object is manipulated or in contact with an environment is also examined. Neural networks (the desired grasping force planner) that generate the humanlike desired grasping force are then designed for robotic systems. The effectiveness of the proposed desired grasping force planner is evaluated via experiments.     

Kinematic modeling of mobile robots by transfer method of augmented generalized coordinates

A kinematic modeling method, which is directly applicable to any type of planar mobile robots, is proposed in this work. Since holonomic constraints have the same differential form as nonholonomic constraints, the instantaneous motion of the mobile robot at current configuration can be modeled as that of a parallel manipulator. A pseudo joint model denoting the interface between the wheel and the ground (i.e., the position of base of the mobile robot) enables the derivation of this equivalent kinematic model. The instantaneous kinematic structures of four different wheels are modeled as multiple pseudo joints. Then, the transfer method of augmented generalized coordinates, which has been popularly employed in modeling of parallel manipulators, is applied to obtain the instantaneous kinematic models of mobile robots. The kinematic models of six different types of planar mobile robots are derived to show the effectiveness of the proposed modeling method. Lastly, for the mobile robot equipped with four conventional wheels, an algorithm estimating a sensed forward solution for the given information of the rotational velocities of the four wheels is discussed. © 2004 Wiley Periodicals, Inc.     

Control of underactuated robot manipulators using switching computed torque method: GA based approach

A new concept for controlling of underactuated robot manipulators is presented by using switching computed torque method. One fundamental feature of the present approach is to use the partly stable controllers (PSCs) in order to fulfill the ultimate control objective. Dynamic model of an underactuated robot system is directly analyzed to synthesize partly stable, computed torque controllers without performing rigorous linearizations or any other deformation methods to the original nonlinear system. Here, we use genetic algorithms (GAs) to employ the optimum control action for a given time frame with the available set of elemental controllers, depending on which links or state variables are controlled, i.e. the selection of optimum switching sequence of the control actions. Two underactuated robot manipulators are taken into consideration so as to illustrate the design procedure. Simulation results show the effectiveness of the proposed method. This basic concept has led authors to explore a vast research area on controlling underactuated manipulators.     

基于CORBA的工业机器人软件框架的研究和应用

在国内首次使用中间件技术,面向机车维护机器人生产线,设计开发可扩展,可升级和可移植的软件应用框架。软件框架的核心是C++ CORBA。试验环境包括2台Motoman UP6机械手和一台Pioneer移动机器人。详细介绍了软件框架的设计和实现,包括采用两层结构实现服务器,框架的技术指标,系统CORBA IDL的具体设计和定义。结论部分规划了今后的研究工作。     

Dynamics and Cooperative Object Manipulation Control of Suspended Mobile Manipulators

Dynamics and control of mobile manipulators is obviously a more challenging problem compared to fixed-base robots. Including a suspension system for these mobile platforms increases their maneuverability, but considerably adds to their complexity. In this paper, a suspended wheeled mobile platform with two 6-DOF Puma-type manipulators is used to manipulate an object along a given path. To apply a model-based control algorithm, it is required to have an explicit dynamics model for such highly nonlinear system. This model should be as concise as possible to include fewer mathematical calculations for online computations. Therefore in this paper, a detailed set of dynamics equations for a multiple arm wheeled mobile platform equipped with an effective suspension system is presented. The method is based on the concept of Direct Path Method (DPM), which is extended here for such challenging type of robots. The obtained dynamics model is then verified with a dynamical analysis study using software ADAMS. Then, Natural Orthogonal Complement Method is used to include the non-holonomic constraint of the wheeled platform in a more concise dynamics model. Next, an impedance control law is applied for cooperative manipulation of an object by the two manipulators. The obtained results for a suspended wheeled platform equipped with two 6-DOF Puma-type manipulators reveal a successful performance for moving an object along a mixed circular-straight path, even in the presence of unexpected disturbing forces, system/end-effector flexibility and impacts due to contact with an obstacle.     

Navigation and learning experiments by an autonomous robot

Developing an autonomous mobile robot capable of navigation, surveillance and manipulation in complex and dynamic environments is a key research activity at CESAR, Oak Ridge National Laboratory's Center for Engineering Systems Advanced Research. The latest series of completed experiments was performed using the autonomous mobile robot HERMIES-IIB (Hostile Environment Robotic Intelligence Experiment Series II-B).