7-DOF Redundant Robot Research Articles

A Robust Visual Servoing Controller for Anthropomorphic Manipulators With Field-of-View Constraints and Swivel-Angle Motion: Overcoming System Uncertainty and Improving Control Performance

Human–robot collaboration has attracted significant attention in the industry due to the flexibility of humans and the accuracy of robots. Humanoid control of anthropomorphic robotic arms combined with visual servoing will enhance the intelligence of industrial robots. However, the robotic manipulator will introduce psychological discomfort to nearby humans, and the loss of visual features will induce visual servoing task failure. Aiming at these problems, this article proposes a humanoid control method based on visual servoing by utilizing the swivel angle derived from the human arm to realize the human-like behavior of anthropomorphic robot manipulators. To advance the visual servoing control performance, a function constraint is designed with the barrier Lyapunov function (BLF) to ensure that image features stay within the field of view (FoV). The sliding mode control (SMC) is combined with image-based visual servoing (IBVS) to dispose of the uncertainties of a seven-degree-of-freedom (7-DoF) redundant robot manipulator. The proposed algorithm is substantiated through comparison experiments based on the Sawyer robot and constructed visual servoing physical platform.

Augmented Reality for 6-DoF Motion Recording, Preview, and Execution to Enable Intuitive Surgical Robot Control

Abstract In robot-assisted surgeries, the surgeon focuses on the surgical tool and its pose, and not on the complete robot’s shape. However, the joints of redundant robots (robots that have more degrees of freedom (DoF) than needed for the positioning of surgical tools) might move in unexpected/undesired ways. Joint motions that lead to patient or collisions are safety critical. We assume that the medical personnel in the operating room can best decide if a planned robot motions come too close to the patient or not. Therefore, we propose an augmented reality-based solution to interact with the robot during surgery planning, and intervention. The tool can be used to command a robot by drawing a trajectory in augmented reality (AR), visualizing the robot movement to check if it is safe before execution. The proposed solution allows surgeons to plan safe robot motion paths before-hand and adapt them when necessary in situ. As a proof-of-concept, we implemented and demonstrated the proposed solution on a 7-DoF redundant robot by commanding different trajectories. The control architecture to plan and execute motion for a surgical robot using AR is a key result of this work.

Kinematic Reliability Analysis of a 7-DOF Redundant Robot

The kinematic reliability of robots, defined as the probability that the end-effector falls inside the specified safe boundary, is of great significance in predicting the accuracy achieved in reality. This work selects the 7 degrees-of-freedom (7-DOF) redundant robot as an example to conduct reliability analysis by utilizing the envelope method against time-related issues in this work. Since variables in industrial robots are very small relative to their means, the motion error functions are commonly linearized by the first-order Taylor’s formula to simplify calculation, and the failure models in all directions and attitude angles are then established through the probability method over the entire input interval. As a result, the actual accuracy of the robot in each pose component will be displayed, instead of merely considering the position error like other scholars. The principle of the proposed method is to transform a time-dependent problem into a time-independent one with the help of the failure extreme points and endpoints, so as to enhance the operation efficiency under the premise of ensuring accuracy. Finally, the simulation results verify that the relative error of the envelope method is less than 6.0% compared with that of the Monte Carlo simulation method, and the computational efficiency is higher than that of the Monte Carlo method, which demonstrates that the envelope method has better comprehensive performance.

Manipulator system designs for drawing random objects through point cloud posture estimation

This paper designed a 7-DOF redundant robot manipulator that can flexibly and efficiently pick-up random objects. The developed 7-DOF machine with an additional redundancy achieved great progress in terms of flexibility and efficiency in the operational space. A robot operating system (ROS) was used to configure the manipulator system’s software modules, supporting convenient system interface, appropriate movement control policy, and powerful hardware device management for better regulation of the manipulator’s motions. A 3D type Point Cloud Library (PCL) was utilized to perform a novel point cloud image pre-processing method that did not only reduce the point cloud number but also maintained the original quality. The results of the experiment showed that the estimation speed in object detection and recognition procedure improved significantly. The redundant robot manipulator architecture with the two-stage search algorithm was able to find the optimal null space. Suitable parameters in D-H transformation of forward kinematics were selected to efficiently control and position the manipulator in the right posture. Meanwhile, the reverse kinematics estimated all angles of the joints through the known manipulator position, orientation, and redundancy. Finally, motion panning implementation of manipulator rapidly and successfully reached the random object position and automatically drew it up to approximate the desired target.

Trajectory tracking control of 7-DOF redundant robot based on estimation of intention in physical human-robot interaction.

Collaborative robot has been widespread application prospect, such as homes, manufacturing, and health-care etc. In physical human-robot interaction, the external force appears inevitably in contact with environment or human, especially the interactive tasks such as trajectory tracking requirements and force compliance control. In this article, a method based on interaction intention estimation, which solve the problem of trajectory tracking accuracy and force compliance control in the same direction for the 7-DOF robot, is proposed. The increased virtual force depended on the manipuility performance index and inverse kinematic solution used the kinematic decoupling method based on the redundant angle avoid the singularity of redundant robot. Then, based on interactive intention estimation, a control strategy of variable impedance sliding mode theory in the presence of virtual force and contact force is proposed to achieve the trajectory tracking. We adopted hyperbolic tangent function to alleviate the chattering problem caused by switch function and validated the control system stability by Lyapunov theorem. Finally, Matlab simulations exhibit a 97.8% of high tracking accuracy amid the external force is 43% less than variable impedance parameters. It is therefore proved that the proposed method can achieve asymptotic tracking and the compliant behavior in physical human-robot interaction.

Calculation of the inverse kinematics solution of the 7-DOF redundant robot manipulator by the firefly algorithm and statistical analysis of the results in terms of speed and accuracy

ABSTRACTIn this study, the inverse kinematics solution of a 7-DOF redundant robot manipulator was performed by using firefly algorithm that is a swarm optimization technique. In order to show the power of this technique, a redundant robotic arm which is inadequate inverse kinematic solution by conventional methods has been chosen. Both speed and accuracy are two important factors in robotic studies. For this reason, the comparison of the method used in this study in terms of speed and accuracy has been carried out in depth. The scenario used is as follows: Firstly, the position equations of this manipulator are derived with the DH parameters. Afterward, the position of the end effector is obtained in the work space according to the forward kinematic calculation. Finally, the joint angles that will be directed to the calculated position values with the least error are obtained by the firefly algorithm and the obtained result is compared with other swarm algorithms such as particle swarm optimization and artificial bee colony.

Task constrained motion planning for 7-degree of freedom manipulators with parameterized submanifolds

PurposeThis paper aims to use the redundancy of a 7-DOF (degree of freedom) serial manipulator to solve motion planning problems along a given 6D Cartesian tool path, in the presence of geometric constraints, namely, obstacles and joint limits.Design/methodology/approachThis paper describes an explicit expression of the task submanifolds for a 7-DOF redundant robot, and the submanifolds can be parameterized by two parameters with this explicit expression. Therefore, the global search method can find the feasible path on this parameterized graph.FindingsThe proposed planning algorithm is resolution complete and resolution optimal for 7-DOF manipulators, and the planned path can satisfy task constraint as well as avoiding singularity and collision. The experiments on Motoman SDA robot are reported to show the effectiveness.Research limitations/implicationsThis algorithm is still time-consuming, and it can be improved by applying parallel collision detection method or lazy collision detection, adopting new constraints and implementing more effective graph search algorithms.Originality/valueCompared with other task constrained planning methods, the proposed algorithm archives better performance. This method finds the explicit expression of the two-dimensional task sub-manifolds, so it’s resolution complete and resolution optimal.

Inverse kinematics of a 7-DOF redundant robot manipulator using the active set approach under joint physical limits

This paper presents a new approach for an online solution of the inverse kinematics problem based on nonlinear optimization for robots with joint physical constraints. The inverse kinematics problem is stated as a constrained nonlinear optimization problem and is solved using Kuhn--Tucker conditions analysis. The nonlinear multivariable optimization problem is locally converted into independent local linear constrained subproblems and each subproblem is analytically solved. For each joint, position limits and velocity limits are considered as physical constraints. The proposed structure benefits from a very low complexity design. The proposed method is fast and requires few calculations. The convergence of the proposed algorithm is proven based on the Lyapunov function. While keeping the algorithm stable, it can navigate the manipulator to a desired position under joint physical limits. The algorithm is simulated on a 7-DOF PA-10 manipulator. Results indicate good efficiency for the proposed structure in constrained path planning of joint space.

Analytical Inverse Kinematics Solver for Anthropomorphic 7-DOF Redundant Manipulators with Human-Like Configuration Constraints

It is a common belief that service robots shall move in a human-like manner to enable natural and convenient interaction with a human user or collaborator. In particular, this applies to anthropomorphic 7-DOF redundant robot manipulators that have a shoulder-elbow-wrist configuration. On the kinematic level, human-like movement then can be realized by means of selecting a redundancy resolution for the inverse kinematics (IK), which realizes human-like movement through respective nullspace preferences. In this paper, key positions are introduced and defined as Cartesian positions of the manipulator's elbow and wrist joints. The key positions are used as constraints on the inverse kinematics in addition to orientation constraints at the end-effector, such that the inverse kinematics can be calculated through an efficient analytical scheme and realizes human-like configurations. To obtain suitable key positions, a correspondence method named wrist-elbow-in-line is derived to map key positions of human demonstrations to the real robot for obtaining a valid analytical inverse kinematics solution. A human demonstration tracking experiment is conducted to evaluate the end-effector accuracy and human-likeness of the generated motion for a 7-DOF Kuka-LWR arm. The results are compared to a similar correspondance method that emphasizes only the wrist postion and show that the subtle differences between the two different correspondence methods may lead to significant performance differences. Furthermore, the wrist-elbow-in-line method is validated as more stable in practical application and extended for obstacle avoidance.

Performance Analysis of Numerical Integration Methods in the Trajectory Tracking Application of Redundant Robot Manipulators

Differential kinematic is one of the most important solution methods in robot kinematics. The main advantage of the differential kinematic method is that it can be easily implemented any kind of mechanisms. Also, an accurate and efficient kinematic based trajectory tracking application can be easily implemented by using this method. In differential kinematic method, we use Jacobian as a mapping operator in the velocity space. Inversion of Jacobian matrix transforms the desired trajectory velocities, which are the linear and angular velocities of the end effector, into the joint velocities. The joint velocities are required to be integrated to obtain the pose of the robot manipulator. This integration can be evaluated by using numerical integration methods, since the inverse kinematic equations are highly complex and nonlinear. Therefore, the performance of the trajectory tracking application of the robot manipulator is directly affected by the chosen numerical integration method. This paper compares the performances of numerical integration methods in the trajectory tracking application of redundant robot manipulators. Several widely used numerical integration methods are implemented into the trajectory tracking application of the 7-DOF redundant robot manipulator named PA-10 and simulation results are given.

A Robust Position and Force Control Strategy for 7-DOF Redundant Manipulators

This paper is concerned with robust position and contact force control for 7-DOF redundant robot arms. An outer-inner loop controller, called the augmented hybrid impedance control scheme is developed. A 6-DOF force/torque sensor is used to measure the interaction forces. These are fed back to the outer-loop controller that implements either a force or an impedance controller in each of the 6 DOF of the tool frame. The force controller is provided with a force set point, and desired inertia and damping are introduced in the force control loop to improve transient performance. The inner loop consists of a Cartesian-level potential difference controller, a redundancy resolution scheme at the acceleration level, and a joint-space inverse dynamics controller. Experimental results for two 7-DOF robot arms (redundant, dextrous, isotropically enhanced, seven-turning pair robot (REDIESTRO) and Mitsubishi PA10-7C) are given to illustrate the performance of the force control strategy. A successful application of the proposed scheme to a surface cleaning task is described using the REDIESTRO, while position and force tracking experiments are described for the Mitsubishi PA10-7C robot.

Self-motion manifolds of a 7-DOF redundant robot arm

The position sub-manifold and orientation sub-man- ifold are defined for the redundant robots in which the end manipulator's position and orientation are decoupled.The end manipulator's workspace is divided into three subspaces accor- ding to the difference of position sub-manifold and orientation sub-manifold.The position sub-manifold and the orientation sub-manifold in all subspaces are expressed as parameter equations by vector algebra,so the self-motion manifold can be obtained as the matched pair that is formed by position sub-manifold and orientation sub-manifold.A simulation is carried out in the first subspace to obtain the self-motion manifolds for a given point,and the result is verified by forward kinematics.The method to solve self-motion manifold with position sub-manifold and orientation sub-manifold is also valid for other kinds of redundant robots in which the end manipulator's position and orientation are decoupled.

Inverse kinematic analysis for cable-driven humanoid-arm manipulator

Based on the current research results of humanoid- arm bionics and parallel manipulators, an approach is presented for 7-DOF cable-driven humanoid-arm manipulator. Cable- driven mechanism is high in mechanism rigidity, controlaccuracy and loading capacity, which overcome the disadv- antages of conventional serial mechanism. The detailed mechanism of humanoid-arm manipulator is introduced firstly; and then the manipulator motion is described by screw theory, the motion ranges of shoulder joint are resolved under the tension conditions of the cables. To find displacement solutions of a 7-DOF redundant robot, a hybrid algorithm, based on GPM and Paden-Kahan sub problems, is proposed. The length of the driven rope can be solved according to the relationship between the joint angles and rope length. The coupling influences from shoulder to the wrist and the elbow joints are also analyzed. As the result, through the simulation of ADAMS, using the straight-line interpolation, real-time animation display is completed for the motion of the manipulator to verify the correctness of inverse kinematics algorithm.

Kinematic control of redundant robots and the motion optimizability measure

This paper treats the kinematic control of manipulators with redundant degrees of freedom. We derive an analytical solution for the inverse kinematics that provides a means for accommodating joint velocity constraints in real time. We define the motion optimizability measure and use it to develop an efficient method for the optimization of joint trajectories subject to multiple criteria. An implementation of the method for a 7-dof experimental redundant robot is present.