Collision-free and smooth joint motion planning for six-axis industrial robots by redundancy optimization

Planning collision-free and smooth joint motion is crucial in robotic applications, such as welding, milling, and laser cutting. Kinematic redundancy exists when a six-axis industrial robot performs five-dimensional tasks, and there are infinite joint configurations for a six-axis industrial robot to realize a cutter location data of the tool path. The robot joint motion can be optimized by taking advantage of the kinematic redundancy, and the collision-free joint motion with minimum joint movement is determined as the optimal. However, most existing redundancy optimization methods do not fully exploit the redundancy of the six-axis industrial robots when they conduct five-dimensional tasks. In this paper, we present an optimization method to solve the problem of inverse kinematics for a six-axis industrial robot to synthesize the joint motion that follows a given tool path, while achieving smoothness and collision-free manipulation. B-spline is applied for the joint configuration interpolation, and the sum of the squares of the first, second, and third derivatives of the B-spline curves are adopted as the smoothness indicators. Besides, the oriented bounding boxes are adopted to simplify the shape of the robot joints, robot links, spindle unit, and fixtures to facilitate collision detections. Dijkstra's shortest path technique and Differential Evolution algorithm are combined to find the optimal joint motion efficiently and avoid getting into a local optimal solution. The proposed algorithm is validated by simulations on two six-axis industrial robots conducting five-axis flank milling tasks respectively.     

Preshaping input trajectories of industrial robots for vibration suppression

This paper presents several novel methods that improve the current input shaping techniques for vibration suppression for multi-degree of freedom industrial robots. Three different techniques, namely, the optimal S-curve trajectory, the robust zero-vibration shaper, and the dynamic zero-vibration shaper, are proposed. These methods can suppress multiple vibration modes of a flexible joint robot under a computed torque control based on a rigid model. The time delays for each method are quantified and compared. The optimal S-curve trajectory finds the maximum jerk to obtain the minimum vibration. The robust zero-vibration shaper can suppress multiple modes without an accurate model. The delay of the dynamic zero-vibration shaper is smaller than the existing input shaping techniques. Our analysis is verified both by simulation and experiment with a six degrees-of-freedom commercial industrial robot.     

Quasi-static path optimization for industrial robots with dress packs

Problems with robot dress packs are a major reason for on-line adjustments of robot programs and down-time in robot stations. It is therefore of high value if the physical behaviour of the dress packs can be considered with simulation methods already during the off-line programming process for a robot station.This paper presents a method for quasi-static path optimization for an industrial robot with respect to its deformable dress pack. Given an initial collision-free path generated by an automatic path planner, the via point configurations of the path are optimized with respect to the performance aspects of the dress pack. The method is derived from a general framework for parameter optimization of a mechanical system subject to quasi-static motions and deformations. The optimal parameter values are obtained from numerical solutions to a non-linear programming problem in which the static equilibrium equations of the system hold at discrete times. Due to the large-scale nature of this problem, a dress pack is modelled as a discrete Cosserat rod, which is the preferred choice for modeling large spatial deformations of a slender flexible structure with coarse discretization.The method is applied to an industrial robot moving in-between stud welding operations in a stud welding station. The optimized path reduces the stress in the dress pack and keeps the dressed robot from the surrounding geometry with a prescribed safety clearance during the entire robot motion.     

Eco-programming of industrial robots for sustainable manufacturing via dynamic time scaling of trajectories

Nowadays, Industrial Robots (IRs) have become widespread in many manufacturing industries. Medium and high payload IRs cover a significant percentage of the overall factory Energy Consumption (EC). This article focuses on the IRs eco-programming to minimize the EC of a robot, being energy efficiency one of the fundamental aims of sustainable manufacturing. By leveraging well-known trajectory scaling methods, this research develops a novel, versatile, fast, and efficient process to define the IR optimal velocity/acceleration profile in time, keeping the geometry of the trajectory fixed. A complete IR system model that founds application in various types of 6 degrees of freedom articulated manipulators has been developed by considering electrical motors, actuator drive systems, and controller cabinet losses. A new optimization technique based on Dynamic Time Scaling of trajectories is presented, and the obtained results are compared with other methods used in the scientific literature. When performing critical path analysis, the EC of the robot system is estimated to be cut down, being the robot motion time fixed, by about 13% through this novel approach. The model has been validated through commercial software, and the proposed optimization algorithm has been implemented in a user-friendly interface tool.     

A parameter identification approach using optimal exciting trajectories for a class of industrial robots

In this paper, the problem of finding optimal exciting trajectories for parameter identification of industrial robots is investigated. A cost function of maximizing the minimum singular value of a recursive matrix is used in the optimization procedure. The optimal exciting trajectories obtained is insensitive with respect to the parameter perturbation. The identification accuracy and convergence speed or parameters is improved.     

Time optimization of the continuous-path motions of industrial robots

This paper presents an engineering approach to the time optimization of robotic motions with specified paths and trapezoidal velocity profiles. Optimizations of this type occur when dealing with continuous-path motions of commercial manipulators. Parameterized path equations and full non-linear robot dynamics are used in conjunction with the actuator limitations and the specified path and velocity profile in order to transform the problem into a non-linear programming form. The optimal velocity profile and the corresponding joint torques/forces are obtained via a simple search algorithm, without resorting to any constrained optimization technique, numerical integration, or search for the switching curve. Three examples of time-optimized robotic motions are presented.     

工业机器人能耗优化方法研究综述

机器人技术作为智能制造的关键,其能耗问题已引起各制造业大国的关注,国内外的研究十分活跃。针对工业机器人能耗优化问题,介绍了轻量化设计、高效驱动系统设计、能量存储和共享装置等低能耗硬件设计方法,从轨迹规划和任务调度方面对能耗优化的软件方法进行了综述,介绍了具有应用潜力的软件优化和硬件相结合的混合方法,同时突出了主要研究成果并说明了不足之处;最后指出工业机器人能耗优化具有潜力的发展趋势。     

Minimum distance collision-free path planning for industrial robots with a prismatic joint

A collision-free path is a path which an industrial robot can physically take while traveling from one location to another in an environment containing obstacles. Usually the obstacles are expanded to compensate for the body width of the robot. For robots with a prismatic joint, which allows only a translational motion along its axis, additional problems created by the long boom are handled by means of pseudoobstacles which are generated by real obstacle's edges and faces. The environment is then modified by the inclusion of pseudoobstacles which contribute to the forbidden regions. This process allows the robot itself again to be represented by a point specifying the location of its end effector in space. An algorithm for determining the shortest distance collision-free path given a sequence of edges to be traversed has been developed for the case of stationary obstacles.     

Posture optimization methodology of 6R industrial robots for machining using performance evaluation indexes

For industrial robots, the relatively low posture-dependent stiffness deteriorates the absolute accuracy in the robotic machining process. Thus, it is reasonable to consider performing machining in the regions of the robot workspace where the kinematic, static and even dynamic performances are highest, thereby reducing machining errors and exhausting the advantages of the robot. Simultaneously, an optimum initial placement of the workpiece with respect to the robot can be obtained by optimizing the above performances of the robot. In this paper, a robot posture optimization methodology based on robotic performance indexes is presented. First, a deformation evaluation index is proposed to directly illustrate the deformation of the six-revolute (6R) industrial robot (IR) end-effector (EE) when a force is applied on it. Then, the kinematic performance map drawn according to the kinematic performance index is utilized to refine the regions of the robot workspace. Furthermore, main body stiffness index is proposed here to simplify the performance index of the robot stiffness, and its map is used to determine the position of the EE. Finally, the deformation map obtained according to the proposed deformation evaluation index is used to determine the orientation of the EE. Following these steps, the posture of the 6R robot with the best performance can be obtained, and the initial workpiece placement can be consequently determined. Experiments on a Comau Smart5 NJ 220-2.7 robot are conducted. The results demonstrate the feasibility and effectiveness of the present posture optimization methodology.     

Image processing system for industrial robots

The image data in a digitized picture can be represented by a set of edge lines and edge-point data. In the system described an object is recognized by comparing its parameters with those of various models. Criteria are given for declaring an object and model to be similar.     

Multiprocessor control system for industrial robots

This paper describes an advanced robot control system based on the three parallel processor boards. The controller has been designed as a general-purpose robot control system dedicated to controlling industrial robots with up to six degrees of freedom. The controller is based on a disk-oriented real-time operating system. The entire set of robot parameters can be monitored and changed by the user on-line. Source files, compilers, linkers and various utilities are provided as well.The main software layers include robot program interpreter, manipulator control facility, robot kinematics, dynamic feed-forward compensation, and digital servos. Basis, hand and joint coordinates are supported. Point-to-point and continuous path motions are provided. Digital and analog IO modules are included for synchronization with an environment. An acquisition system for monitoring and graphical presentation of robot coordinates, velocities and IO signals is provided. The paper ends with some experimental results for a six-degree of freedom robot.     

Optimal trajectory planning for industrial robots

An analysis of the results of an algorithm for optimal trajectory planning of robot manipulators is described in this paper. The objective function to be minimized is a weighted sum of the integral squared jerk and the execution time. Two possible primitives for building the trajectory are considered: cubic splines or fifth-order B-splines. The proposed technique allows to set constraints on the robot motion, expressed as upper bounds on the absolute values of velocity, acceleration and jerk. The described method is then applied to a 6-d.o.f. robot (a Cartesian gantry manipulator with a spherical wrist); the results obtained using the two different primitives are presented and discussed.     

A new methodology for joint stiffness identification of heavy duty industrial robots with the counterbalancing system

This paper deals with the joint stiffness modeling and identification of the heavy duty industrial robot with the counterbalancing system (CBS), which is important for the workspace optimization and deflection compensation in the robotic manufacturing. Shortcomings of the traditional method for the joint stiffness modeling and corresponding identification are analyzed in this paper. Motivated by the advantage and limitations of the traditional approach, a new identification methodology based on the servo motor current and corresponding position deflection is proposed to obtain the accurate joint stiffness. To validate the effectiveness of the proposed method for the joint stiffness modeling and identification, an identification and validation experiment is carried out using the HH-150 heavy duty industrial robot. The results show that the proposed methodology is able to identify the joint stiffness of the heavy duty industrial robot with the CBS, and the proposed new methodology outperforms in terms of accuracy, convenience and efficiency for the joint stiffness identification.     

An observer for flexible joint robots

The problem of state observation of robots that have elastic joints is discussed. Outputs are assumed to be the global link coordinates and their time derivatives, and a nonlinear observer is proposed which asymptotically reconstructs all the robot state variables. The dynamic behaviour of the observation algorithm is illustrated by simulation tests referred to a manipulator with three revolute elastic joints. To verify the observer robustness, the previous simulation tests were repeated by using the same observer, designed for a nominal payload of 5 kg, and actual robot payloads of 0 and 10 kg. The differences with respect to the nominal case are not appreciable. However, the steady-state joint errors, which were about 10^-6 rad in the nominal case, became about 10^-4 rad     

A path planning algorithm for industrial robots

Instead of using the tedious process of robot teaching, an off-line path planning algorithm has been developed for industrial robots to improve their accuracy and efficiency. Collision avoidance is the primary concept to achieve such goal. By use of the distance maps, the inspection of obstacle collision is completed and transformed to the configuration space in terms of the robot joint angles. On this configuration map, the relation between the obstacles and the robot arms is obvious. By checking the interference conditions, the collision points are indicated with marks and collected into the database. The path planning is obtained based on the assigned marked number of the passable region via wave expansion method. Depth-first search method is another approach to obtain minimum sequences to pass through. The proposed algorithm is experimented on a 6-DOF industrial robot. From the simulation results, not only the algorithm can achieve the goal of collision avoidance, but also save the manipulation steps.     

Base frame calibration for coordinated industrial robots

To solve the problem of base frame calibration for coordinated multi-robot system, a new method is proposed in this paper. It is carried out through a series of “handclasp” manipulations between two coordinated robots, then a preliminary result can be reached by the calibrating equation. After that, in order to make sure that the calibrated rotation matrix is orthonormal, an optimal estimation of the relative rotation between the base frames of coordinated manipulators is solved out under the criterion of optimal Frobenius norm approximation. By the quaternion representation for rotation matrix and the Lagrange Multiplier method, an orthonormal matrix can be reached which is just the unknown calibrating result for base frames of the coordinated robots. Simulation and experiment results have verified the validity and effectiveness of the proposed method.     

Holographic measurement of industrial robots

Application and/or user's demand on industrial robot performance is increasing rapidly. Higher positioning accuracy, payload capability, speed, larger working area, etc. are required, mostly depending on the application. Demand will be even higher in the future.In some manufacturing system application, e.g. material handling and assembly, the positioning accuracy of industrial robots is sometimes not adequate. At the same time, in the latter case, higher speeds are desired. As the case is similar in many areas, utilization of robots to perform manufacturing operations is accelerating each day. Therefore, higher performance characteristics are desired.To increase the positioning accuracy of robots, factors degrading accuracy must be detected and, if possible, eliminated or minimized. In this paper load-induced inaccuracy for an industrial robot is investigated and a compensation algorithm for the deflection is derived to improve the positioning accuracy.     

Impedance control of industrial robots

Manipulation fundamentally requires the manipulator to be mechanically coupled to the object being manipulated. A consideration of the physical constraints imposed by dynamic interaction shows that control of a vector quantity such as position or force is inadequate and that control of the manipulator impedance is necessary. Techniques for planning and control of manipulator behavior are presented which result in a unified approach to target acquisition, obstable avoidance, kinematically constrained motion, and dynamic interaction. A feedback control algorithm for implementing a cartesian end-point impedance on a nonlinear manipulator is presented. The modulation of end-point impedance independent of feedback is also considered. A method for choosing the impedance appropriate to a task using optimization theory is discussed.