An Analytical Method for Decoupled Local Smoothing of Linear Paths in Industrial Robots

The linear-format path is widely adopted to approximate the continuous contour in robot controllers. The tangential discontinuity of the linear paths usually causes the discontinuity of the joint velocity. To comply with the joint kinematics limits, the robots have to stop at each corner point, resulting in a great loss of efficiency. To achieve a smooth motion, this paper presents an analytical decoupled C³ continuous local path smoothing method for industrial robots. The tool position path is smoothed in the reference frame while the tool orientation is smoothed in the rotation parametric space based on the exponential coordinates of rotations. The quintic B-splines are inserted at the corners of the linear segments to achieve the G³ continuity of the tool position path and tool orientation path. The orientation smoothing error is constrained analytically. By reparameterization of the remaining linear segments using specially constructed B-splines, the C³ continuity of the tool position path and tool orientation path is achieved. Then, the synchronization of the tool orientation path and tool position path can be guaranteed by sharing the same curve parameter. Besides, to improve the smoothness of the angular motion on the remaining linear segments during parameter synchronization, the transition lengths of the inserted B-splines are optimized. The proposed local smoothing method guarantees that the generated smooth orientation path in the rotation space is invariant with the selection of the reference frame and the orientation of the tool frame, and ensures the jerk-continuous motion with a smoother angular motion on the remaining linear segments, which could improve the motion smoothness of the tool path and tracking accuracy. The effectiveness of the proposed method is validated through simulation and experiments.     

Adaptive control of redundant multiple robots in cooperative motion

A redundant robot has more degrees of freedom than what is needed to uniquely position the robot end-effector. In practical applications the extra degrees of freedom increase the orientation and reach of the robot. Also the load carrying capacity of a single robot can be increased by cooperative manipulation of the load by two or more robots. In this paper, we develop an adaptive control scheme for kinematically redundant multiple robots in cooperative motion.In a usual robotic task, only the end-effector position trajectory is specified. The joint position trajectory will therefore be unknown for a redundant multi-robot system and it must be selected from a self-motion manifold for a specified end-effector or load motion. In this paper, it is shown that the adaptive control of cooperative multiple redundant robots can be addressed as a reference velocity tracking problem in the joint space. A stable adaptive velocity control law is derived. This controller ensures the bounded estimation of the unknown dynamic parameters of the robots and the load, the exponential convergence to zero of the velocity tracking errors, and the boundedness of the internal forces. The individual robot joint motions are shown to be stable by decomposing the joint coordinates into two variables, one which is homeomorphic to the load coordinates, the other to the coordinates of the self-motion manifold. The dynamics on the self-motion manifold are directly shown to be related to the concept of zero-dynamics. It is shown that if the reference joint trajectory is selected to optimize a certain type of objective functions, then stable dynamics on the self-motion manifold result. The overall stability of the joint positions is established from the stability of two cascaded dynamic systems involving the two decomposed coordinates.     

Development of CAM system based on industrial robotic servo controller without using robot language

This paper describes the development of a robotic CAM system for an articulated industrial robot RV1A from the view point of robotic servo controller. It is defined here that the CAM system includes an important function which allows an industrial robot to move along cutter location data (CL data) consisting of position and orientation components. In addition, the developed CAM system has a high applicability to other industrial robots whose servo systems are technically opened to end-users. The developed robotic CAM system works as a straightforward interface between a general CAD/CAM and an industrial robot. At the present stage, the relationship between CAD/CAM and industrial robots is not well established compared to NC machine tools that are widely spread in manufacturing industries. The CAM systems for NC machine tools are already established, however, the CAM system for industrial robots has not been sufficiently considered and developed yet. A teaching pendant is generally used to obtain position and orientation data of the arm tip before an industrial robot works. Here, in order to enhance the relationship between a conventional CAD/CAM system and an industrial robot, a simple and straightforward CAM system without using any robot language is developed and implemented. The basic design of the robotic CAM system and the experimental results are presented in this paper.     

Neural-network-based two-loop control of robotic manipulators including actuator dynamics in task space

A neural-network-based motion controller in task space is presented in this paper. The proposed controller is addressed as a two-loop cascade control scheme. The outer loop is given by kinematic control in the task space. It provides a joint velocity reference signal to the inner one. The inner loop implements a velocity servo loop at the robot joint level. A radial basis function network （RBFN） is integrated with proportional-integral （PI） control to construct a velocity tracking control scheme for the inner loop. Finally, a prototype technology based control system is designed for a robotic manipulator. The proposed control scheme is applied to the robotic manipulator. Experimental results confirm the validity of the proposed control scheme by comparing it with other control strategies.     

Dynamic visual servo control of a 4-axis joint tool to track image trajectories during machining complex shapes

A large part of the new generation of computer numerical control systems has adopted an architecture based on robotic systems. This architecture improves the implementation of many manufacturing processes in terms of flexibility, efficiency, accuracy and velocity. This paper presents a 4-axis robot tool based on a joint structure whose primary use is to perform complex machining shapes in some non-contact processes. A new dynamic visual controller is proposed in order to control the 4-axis joint structure, where image information is used in the control loop to guide the robot tool in the machining task. In addition, this controller eliminates the chaotic joint behavior which appears during tracking of the quasi-repetitive trajectories required in machining processes. Moreover, this robot tool can be coupled to a manipulator robot in order to form a multi-robot platform for complex manufacturing tasks. Therefore, the robot tool could perform a machining task using a piece grasped from the workspace by a manipulator robot. This manipulator robot could be guided by using visual information given by the robot tool, thereby obtaining an intelligent multi-robot platform controlled by only one camera.     

Time-optimal tool motion planning with tool-tip kinematic constraints for robotic machining of sculptured surfaces

A time-optimal motion planning method for robotic machining of sculptured surfaces is reported in this paper. Compared with the general time-optimal robot motion planning, a surface machining process provides extra constraints such as tool-tip kinematic limits and complexity of the curved tool path that also need to be taken into account. In the proposed method, joint space and tool-tip kinematic constraints are considered. As there are high requirements for tool path following accuracy, an efficient numerical integration method based on the Pontryagin maximum principle is adopted as the solver for the time-optimal tool motion planning problem in robotic machining. Nonetheless, coupled and multi-dimensional constraints make it difficult to solve the problem by numerical integration directly. Therefore, a new method is provided to simplify the constraints in this work. The algorithm is implemented on the ROS (robot operating system) platform. The geometry tool path is generated by the CAM software firstly. And then the whole machine moving process, i.e. the feedrate of machining process, is scheduled by the proposed method. As a case study, a sculptured surface is machined by the developed method with a 6-DOF robot driven by the ROS controller. The experimental results validate the developed algorithm and reveal its advantages over other conventional motion planning algorithms for robotic machining.     

表征空间中的机器人分层运动规划

由于对机器人的任务要求日趋复杂和多变,如何使机器人具备灵活的配置和运动规划能力,以适应复杂任务的需求,成为了目前运动规划领域所研究的核心问题.传统的基于任务空间和配置空间的建模方法虽然在机器人运动规划领域得到了非常广泛的应用,但在用于解决复杂规划任务时无法对不可行任务进行进一步地处理.本文在表征空间模型的基础上,提出了一种分层的运动规划算法,一方面借助于表征空间维度的扩展,使对运动规划任务的描述更为灵活;另一方面通过任务层与运动层的循环交互,使生成的路径满足更高层次和更丰富的任务要求.在仿人机器人和多机器人系统上的应用结果表明了本文所提算法的有效性.     

A Constraint-Based Robotic Soccer Team

It is a challenging task for a team of multiple fast-moving robots to cooperate with each other and to compete with another team in a dynamic, real-time environment. For a robot team to play soccer successfully, various technologies have to be incorporated including robotic architecture, multi-agent collaboration and real-time reasoning. A robot is an integrated system, with a controller embedded in its plant. A robotic system is the coupling of a robot to its environment. Robotic systems are, in general, hybrid dynamic systems, consisting of continuous, discrete and event-driven components. Constraint Nets (CN) provide a semantic model for modeling hybrid dynamic systems. Controllers are embedded constraint solvers that solve constraints in real-time. A controller for our robot soccer team, UBC Dynamo98, has been modeled in CN, and implemented in Java, using the Java Beans architecture. A coach program using an evolutionary algorithm has also been designed and implemented to adjust the weights of the constraints and other parameters in the controller. The results demonstrate that the formal CN approach is a practical tool for designing and implementing controllers for robots in multi-agent real-time environments. They also demonstrate the effectiveness of applying the evolutionary algorithm to the CN-modeled controllers.     

Direct Virtual-hand Interface in Robot Assembly Programming

For a long time, robot assembly programming has been produced in two environments: on-line and off-line. On-line robot programming uses the actual robot for the experiments performing a given task; off-line robot programming develops a robot program in either an autonomous system with a high-level task planner and simulation or a 2D graphical user interface linked to other system components. This paper presents a whole hand interface for more easily performing robotic assembly tasks in the virtual tenvironment. The interface is composed of both static hand shapes (states) and continuous hand motions (modes). Hand shapes are recognized as discrete states that trigger the control signals and commands, and hand motions are mapped to the movements of a selected instance in real-time assembly. Hand postures are also used for specifying the alignment constraints and axis mapping of the hand-part coordinates. The basic virtual-hand functions are constructed through the states and modes developing the robotic assembly program. The assembling motion of the object is guided by the user immersed in the environment to a path such that no collisions will occur. The fine motion in controlling the contact and ending position/orientation is handled automatically by the system using prior knowledge of the parts and assembly reasoning. One assembly programming case using this interface is described in detail in the paper.     

A design of a controller as a component of a robotic manufacturing system

This paper specifies the functional design of a robot or machine tool controller suitable for inclusion in robotic manufacturing systems. The principle interest is the unmanned manufacturing cells which are being developed as major components of new manufacturing facilities. The functional specifications are motivated by recent experiences with the creation of a prototype cell for an open die forging process. There are two key technical design requirements. The first relates to the robot or machine tool being controlled. The controller must direct the machine actions, and, for unmanned operation, the controller must receive and process sensor information for process modification and for fault tolerance. The second relates to communication with the central cell computer (the host). The operation of an unmanned system requires a robot communication channel between the host and the controller; the controller must also respond to a variety of instructions transmitted from the host. Additional controller design requirements are imposed by economics. The proposed controller can be used today, and can develop in an evolutionary manner to meet the needs of future manufacturing systems. The evolutionary development is made possible by modular design, organized in a hierarchical manner.     

Task space control of a welding robot using a fuzzy coordinator

This paper introduces a fuzzy coordinator as a novel application of fuzzy controller. A control transformation from the task space to the joint space is required to control a robot manipulator in the task space. Because the actuators operate in the joint space while the manipulator is controlled in the task space. A conflict between two spaces is produced due to using an imprecise transformation. Fuzzy coordinator coordinates two spaces by modifying the control transformation affected by uncertainties. The fuzzy coordinator is designed simply and operates as a robust controller. The role of fuzzy coordinator is analyzed and illustrated in the robust control of a welding robot in the task space. A circular trajectory is planned for a welding task performed by a SCARA robot. The fuzzy coordinator is then used to improve the performance of control system affected by imprecise transformations including the imprecise path transformation and the approximated feedback linearization.     

Energy analysis of robot task motions

An energy criterion for choosing the best type of manipulator for a specified task is developed. First, the energy required to perform the robotic task is calculated. Then the lower bound of the mechanical energy consumed by the various kinds of manipulators during their motion, while performing a task, is calculated. Thus, the efficiency of a manipulator for the task is determined. Some examples show that the proper selection of the manipulator configuration can reduce the required energy to a quarter of that of a less suitable one. Once the most suitable manipulator is chosen, the criterion for its most energy efficient motion is developed. The model takes into account the kinematic configuration of the robot, gravitational and other external and internal forces acting on the robot during its operation, and the electric motor driving the robot links. Energy optimization of different paths of motion in joint coordinates is discussed briefly.     

Augmented reality-assisted robot programming system for industrial applications

Robots are important in high-mix low-volume manufacturing because of their versatility and repeatability in performing manufacturing tasks. However, robots have not been widely used due to cumbersome programming effort and lack of operator skill. One significant factor prohibiting the widespread application of robots by small and medium enterprises (SMEs) is the high cost and necessary skill of programming and re-programming robots to perform diverse tasks. This paper discusses an Augmented Reality (AR) assisted robot programming system (ARRPS) that provides faster and more intuitive robot programming than conventional techniques. ARRPS is designed to allow users with little robot programming knowledge to program tasks for a serial robot. The system transforms the work cell of a serial industrial robot into an AR environment. With an AR user interface and a handheld pointer for interaction, users are free to move around the work cell to define 3D points and paths for the real robot to follow. Sensor data and algorithms are used for robot motion planning, collision detection and plan validation. The proposed approach enables fast and intuitive robotic path and task programming, and allows users to focus only on the definition of tasks. The implementation of this AR-assisted robot system is presented, and specific methods to enhance the performance of the users in carrying out robot programming using this system are highlighted.     

Economic analysis of robotic operations: A case study of a thermal spraying robot

There is growing interest in the industrial applications of computer-integrated manufacturing (CIM) and robotic technology. The economic analysis methods which are currently available to assess the cost effectiveness of robotic systems are, however, limited. This paper presents a methodology to address this issue. To demonstrate the methodology, a case-study is presented which uses a thermal spraying robot in a rapid tool manufacturing system. The interdependencies between tolerance, robot accuracy, and the probability of a successful spraying operation are demonstrated. The economic effects of using robots in the spraying process are analyzed. Analytical models are developed to estimate the productivity of components without any defects and the improvement in tool life attributable to robotic spraying. The economic analysis method presented in the paper is also applicable to other operations such as robotic assembly and robotic welding.     

A Neuro-Sliding Mode Control Scheme for Constrained Robots with Uncertain Jacobian

The joint robot control requires to map desired cartesian tasks into desired joint trajectories, by using the ill-posed inverse kinematics mapping. In order to avoid inverse kinematics, the control problem is formulated directly in task space to gives rise to cartesian robot control. In addition, when the robot is constrained due to its kinematic mappings yields a stiff system and an additional complexity arises to implement cartesian control for constrained robots. In this paper, an alternative approach is proposed to guarantee global convergence of force and position cartesian tracking errors under the assumption that the jacobian is not exactly known. A neuro-sliding mode controller is presented, where a small size adaptive neural network compensates approximately for the inverse dynamics and an inner control loop induces second order sliding modes to guarantee tracking. The sliding mode variable tunes the online adaptation of the weights. A passivity analysis yields the energy Lyapunov function to prove boundedness of all closed-loop signals and variable structure control theory is used to finally conclude convergence of position and force tracking errors. Experimental results are provided to visualize the expected performance.     

Optimization of layout and path planning of surgical robotic system

Positioning a surgical robot for optimal operation in a crowded operating room is a challenging task. In the robotic-assisted surgical procedures, the surgical robot’s end-effector must reach the patient’s anatomical targets because repositioning of the patient or surgical robot requires additional time and labor. This paper proposes an optimization algorithm to determine the best layout of the operating room, combined with kinematics criteria and optical constraints applied to the surgical assistant robot system. A new method is also developed for trajectory of robot’s end-effector for path planning of the robot motion. The average deviations obtained from repeatability tests for surgical robot’s layout optimization were 1.4 and 4.2 mm for x and y coordinates, respectively. The results of this study show that the proposed optimization method successfully solves the placement problem and path planning of surgical robotic system in operating room.

     

Nonlinear formation control of unicycle-type mobile robots

We investigate formation control of a group of unicycle-type mobile robots at the dynamics level with a little amount of inter-robot communication. A combination of the virtual structure and path-tracking approaches is used to derive the formation architecture. Each individual robot has only position and orientation available for feedback. For each robot, a coordinate transformation is first derived to cancel the velocity quadratic terms. An observer is then designed to globally exponentially/asymptotically estimate the unmeasured velocities. An output feedback controller is designed for each robot. The controller is designed in such a way that the path derivative is left as a free input to synchronize the robots’ motion. Simulations illustrate the soundness of the proposed controller.     

Skill learning framework for human–robot interaction and manipulation tasks

In this article, a learning framework that enables robotic arms to replicate new skills from human demonstration is proposed. The learning framework makes use of online human motion data acquired using wearable devices as an interactive interface for providing the anticipated motion to the robot in an efficient and user-friendly way. This approach offers human tutors the ability to control all joints of the robotic manipulator in real-time and able to achieve complex manipulation. The robotic manipulator is controlled remotely with our low-cost wearable devices for easy calibration and continuous motion mapping. We believe that our approach might lead to improving the human-robot skill learning, adaptability, and sensitivity of the proposed human-robot interaction for flexible task execution and thereby giving room for skill transfer and repeatability without complex coding skills.     

Inverse velocity analysis for line guidance five-axis robots

In this paper, inverse velocity problem for five-axis robots is investigated. The conventional method for a five-axis robot is to pseudo-inverse the 6×5 Jacobian matrix. The solution, primarily based on six freedoms inverse velocity analysis, is just an approximation with a least-square error. A five-axis robot can exactly guide an axis-symmetrical tool in 3-D space. Two exact solutions are provided for five-axis robots. One is based on the screw motion of the tool. The other is based on spherical angles of the tool to derive a 5×5 Jacobian matrix. A new type of singular configuration is discovered and is called the task singularity. The moving path of the line shaped tool is constructed as a ruled surface. Analysis of the angular acceleration shows the surface constructed based on the spherical angle representation has better characteristic. It is concluded that for five-axis robots, the tool position is better represented by five parameters rather than six parameters in order to get better solutions for inverse velocity as well as the motion planning.     

Multi-rigid-body dynamics and online model predictive control for transformable multi-links aerial robot*

Transformable multi-links aerial robots have great potentials in application relying on the transformable features to change its shape during the flight. Compared to traditional quadrotor robots, transformable multi-links robots are equipped with servo motor between links. To simplify the non-linear dynamic system, the previous work restricts the robot to transform in very slow speed so that the robot could be approximated as a quadrotor robot at each time point. However, tradeoff comes as the dynamic performance is given up. In this paper, we come up with a new framework combining of computationally efficient non-linear model predictive controller and motion primitive to optimize thrust force and joints trajectory of the multi-links aerial robot. Finally, we verify our framework with fast transformation motions and table tennis task which requires dynamic performance.