Dual Manipulator System Research Articles

A Self-Collision Detection Algorithm of a Dual-Manipulator System Based on GJK and Deep Learning.

Self-collision detection is fundamental to the safe operation of multi-manipulator systems, especially when cooperating in highly dynamic working environments. Existing methods still face the problem that detection efficiency and accuracy cannot be achieved at the same time. In this paper, we introduce artificial intelligence technology into the control system. Based on the Gilbert-Johnson-Keerthi (GJK) algorithm, we generated a dataset and trained a deep neural network (DLNet) to improve the detection efficiency. By combining DLNet and the GJK algorithm, we propose a two-level self-collision detection algorithm (DLGJK algorithm) to solve real-time self-collision detection problems in a dual-manipulator system with fast-continuous and high-precision properties. First, the proposed algorithm uses DLNet to determine whether the current working state of the system has a risk of self-collision; since most of the working states in a system workspace do not have a self-collision risk, DLNet can effectively reduce the number of unnecessary detections and improve the detection efficiency. Then, for the working states with a risk of self-collision, we modeled precise colliders and applied the GJK algorithm for fine self-collision detection, which achieved detection accuracy. The experimental results showed that compared to that with the global use of the GJK algorithm for self-collision detection, the DLGJK algorithm can reduce the time expectation of a single detection in a system workspace by 97.7%. In the path planning of the manipulators, it could effectively reduce the number of unnecessary detections, improve the detection efficiency, and reduce system overhead. The proposed algorithm also has good scalability for a multi-manipulator system that can be split into dual-manipulator systems.

A Sampling-Based Unfixed Orientation Search Method for Dual Manipulator Cooperative Manufacturing.

The case of dual manipulators with shared workspace, asynchronous manufacturing tasks, and independent objects is named a dual manipulator cooperative manufacturing system, which requires collision-free path planning as a vital issue in terms of safety and efficiency. This paper combines the mathematical modeling method with the time sampling method in the classification of robot path-planning algorithms. Through this attempt we can achieve an optimal local search path during each sampling period interval. Our strategy is to build the corresponding non-linear optimization functions set based on the motion characteristics of the dual manipulator system. In this way, the path-planning problem can be turned into a purely mathematical problem of solving the non-linear optimization programming equations set. The spatial geometric analysis is used to linearize the predicted dual-manipulator minimum distance equation, thus linearizing the non-linear optimization equations set. Finally, this system of linear optimization equations will be mapped directly into a virtual Euclidean space and then solved intuitively using the spatial geometry theory. By simulation and comparing with the previous strategies, we find that the planning results of the newly proposed planning strategy are smoother and have shorter deviations as well as a higher algorithmic efficiency in terms of spatial geometric properties.

Dual manipulator system calibration based on virtual constraints

Dual manipulator system calibration based on virtual constraints

Dual manipulator system of the field hot-line working robot in 110-kV substations

PurposeThe purpose of this paper is to present a dual manipulator system for aloft hot-line assembly tasks of connection fittings in 110-kv intelligent substation, which is significant to the research on hot-line working robots.Design/methodology/approachThis paper addresses the challenges of the task and presents a dual manipulator system which can overcome these challenges to realize the robotic assembly of connection fittings in narrow space without impacting the safe distance of both phase to phase and phase to ground. Two manipulators share a same global reference coordinate. The mission of Manipulator 1 is to position the fixed part of connection fittings and screw the bolts on it. Visual computing provides the approximately position for the end-effector of Manipulator 2, after which The Manipulator 2 carries the removable part of connection fittings to this position. Then, the assembly task could be completed with the posture of the Manipulator 2 adjusted following the guidance by force-position control.FindingsThe dual manipulator system can position the target under different illumination conditions and complete fast assembly of connect fittings in 110-kV substation. No strong arc discharge or surface erosion phenomenon has been observed.Practical implicationsThis dual manipulator system will be particularly useful for the hot-line assembly of connection fittings in 110-kv intelligent substation, as well as some assembly tasks where uncertain target position and complex contact surface such as cylindrical hole is involved.Originality/valueThis study presents a dual manipulator system used by a field robot working in 110-kv intelligent substation. The system is able to achieve the connection fittings assembly task under energized simulation experimental system. Unlike other peg-in-hole assembly strategy, it does not require high stability of manipulator or plane contact surface around the hole.

Adaptive Region Boosting method with biased entropy for path planning in changing environment

Path planning in changing environments with difficult regions, such as narrow passages and obstacle boundaries, creates significant challenges. As the obstacles in W-space move frequently, the crowd degree of C-space changes accordingly. Therefore, in order to dynamically improve the sampling quality, it is appreciated for a planner to rapidly approximate the crowd degree of different parts of the C-space, and boost sample densities with them based on their difficulty levels. In this paper, a novel approach called Adaptive Region Boosting (ARB) is proposed to increase the sampling density for difficult areas with different strategies. What's more, a new criterion, called biased entropy, is proposed to evaluate the difficult degree of a region. The new criterion takes into account both temporal and spatial information of a specific C-space region, in order to make a thorough assessment to a local area. Three groups of experiments are conducted based on a dual-manipulator system with 12 DoFs. Experimental results indicate that ARB effectively improves the success rate and outperforms all the other related methods in various dynamical scenarios.

Narrow Passage Watcher for Safe Motion Planning by Using Motion Trend Analysis of C-Obstacles

Finding safe paths for robots in changing environments is a significant issue for motion planning. However, it could be fairly difficult when there are narrow passages in the configuration space. Solutions to this problem can be appli- cable to not only mobile robots but also other domains such as computer animation and computational biology. This paper presents a novel method called Narrow Passage Watcher (NPW) to cope with narrow passage issues in changing envi- ronments. It approximately predicts the variation trend of narrow passages and analyzes their security and thus guides safe path planning. Meanwhile, a supporting hybrid boost strategy is presented to increase the sampling density inside narrow passages with different variation trend. Compared with existing work, the predictive mechanism provided by NPW gives the planner foresight so that it can find safer paths in changing environments with a higher success rate. Experiments con- ducted with a dual-manipulator system with 12 DOFs show that NPW can reduce the number of replanning times and to- tal planning time remarkably as well as improving the success rate of path planning.

A study on co‐operative motion planning of a dual manipulator system for measuring radioactivity

PurposeThe aim of this paper is to describe how to make a co‐operative motion plan for a dual manipulator system to measure the radioactivity of wastes produced in decommissioning a nuclear power plant.Design/methodology/approachThe system consists of two tasks: the main task generates the path of the measuring operation and the subtask maintains a good working position by co‐operative motion of the two manipulators.FindingsA dual manipulator system requires an effective indicator of the current working position for the realisation of flexible co‐operative motion. Extended manipulability, which takes the motion limit of each joint angle into consideration, is shown to be an effective indicator.Originality/valueExtended manipulability, which shows the motion possible from the current configuration, is offered as an improvement on conventional manipulability.

Singularity-Robust Inverse Kinematics Using Lagrange Multiplier for Redundant Manipulators

In this paper, a singularity-robust inverse kinematics is newly suggested by using a Lagrange multiplier for redundant manipulator systems. Two tasks are considered with priority orders under the assumption that a primary task has no singularity. First, an inverse kinematics problem is formulated to be an optimization one subject to an equality constraint, in other words, to be a minimization problem of secondary task error subject to an equality constraint for primary task execution. Second, in the procedure of minimization for a given objective function, a new inverse kinematics algorithm is derived. Third, since nonzero Lagrange multiplier values appear in the neighborhood of a singular configuration of a robotic manipulator, we choose them as a natural choice of the dampening factor to alleviate the ill-conditioning of matrix inversion, ultimately for singularity-robust inverse kinematics. Finally, the effectiveness of the suggested singularity-robust inverse kinematics is shown through a numerical simulation about deburring and conveyance tasks of a dual arm manipulator system.

Acceleration and torque redistribution for a dual-manipulator system

Recent research has considered robotic machining as an alternative to traditional computer numerical control machining, particularly for prototyping applications. However, unlike traditional machine tools, robots are subject to relatively larger dynamic disturbances and operate closer to their torque limits. These factors, combined with inaccurate manipulator and machining process models, can cause joint actuator saturation during operation. This paper presents a trajectory planner that will reduce torques that are near saturation by generating trajectories with a weighted pseudoinverse. Using a relative Jacobian, the tool path is resolved into joint trajectories at the acceleration level. This paper presents a new method for selecting the weighting matrix based on the proximity of the joint torques to saturation limits. This weighting reduces the joint accelerations contributing the most to the torques near saturation, thereby reducing the joint torques. The accelerations of other joints increase to satisfy the increased demand. The effectiveness of the acceleration and torque redistribution algorithm has been demonstrated via extensive simulations.

10213 双腕マニピュレータによる板金曲げ加工に関する研究((IV),OS15 知能ロボット)

In this study the method which generates the working plan of a dual manipulator system for robotic sheet metal bending is proposed. In work planning for robotic sheet metal bending, grasping position and reposition timing must be determined and co-operative movement between left- and right-side manipulator is required in order to realize the efficient operation. In the proposed method, the best grasping positions and the reposition timings are determined based on the single manipulator operation and a smart co-operative motion is realized. Computer simulation is carried out based on the proposed method and illustrative examples and results of simulation are given. The effectiveness of this method is discussed.

Flexible Rope Manipulation Using Elastic Deformation Modeling by Dual Manipulator System with Vision Sensor

In this paper we propose a flexible object manipulation method by a dual manipulator system. A flexible object such a rope and paper is easily deformed and has hysteresis. Various approaches have been made on the research for the flexible object manipulation. However in the former research works, the manipulator system works only simple task. For more complex works with flexible object, the robot has to hand over the flexible object. So, we propose a flexible object recognition method which can hand over a flexible object using vision information and flexible object model. The dual manipulator system tied a cylinder object with flexible rope by repeating handing over actions in the experiment.

冗長双腕マニピュレータ系の準最短時間軌道計画法

This paper describes a method for sub-minimal-time trajectory planning of a dual manipulator system required to move a rigid task object from one spatial point to another. In this method, in order to transform the time optimal control problem into a non-linearly constrained optimisation problem, a piece-wise constant function is used to approximate the third derivatives of the generalised coordinates of the active joints of the dual manipulator system. However, the system is underspecified due to the redundancy, which is inherent to the system. A technique to overcome the problem, in which an excessive torque is used as optimisation variables, is proposed accordingly. A numerical example involving two SCARA type manipulators handling a long beam was used to illustrate the proposed scheme and results showed the effectiveness of the proposed technique.

Kinematic identification of multi-jointed payloads

An algorithm is presented that identifies the kinematics of an unknown payload with multiple degrees-of-freedom. Using a dual manipulator system, manipulator joint angles are collected from which end-effector positions and orientations are inferred. The position data are used to calculate vectors normal to the constraint surface dictated by the payload. These normal vectors, along with the orientation data, are used to determine the types of joints in the payload, and then the payload's kinematic structure. Once the structure is known, the kinematic parameters are calculated using vector geometry. Payloads with up to two joints are analyzed and simulation results are provided.

Coordinated control of multiple manipulator systems

A scheme for controlling multimanipulator systems is presented. The control objective is to coordinate the manipulators to perform parts-matching tasks such as screwing a nut onto a bolt. The task of moving a rigid object can be treated as a special case. Two secondary control objectives, internal force control and load distribution, can be accomplished within the structure of the control law. The internal force control mechanism keeps the internal forces on the object being manipulated at a desirable level. The load distribution mechanism distributes control effort to each manipulator according to a weighting factor. It is also shown that the control algorithm has a modular structure which facilitates its implementation on a multiprocessor computer. The scheme was tested on a planar scara type dual-manipulator system. A series of experimental results is included to demonstrate the system performance under various conditions.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>