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SUMMARYThis paper proposes a vision-based kinematic analysis and kinematic parameters identification of the proposed architecture, designed to perform the object catching in the real-time scenario. For performing the inverse kinematics, precise estimation of the link lengths and other parameters needs to be present. Kinematic identification of Delta based upon Model10 implicit model with ten parameters using the iterative least square method is implemented. The loop closure implicit equations have been modelled. In this paper, a vision-based kinematic analysis of the Delta robots to do the catching is discussed. A predefined library of ArUco is used to get a unique solution of the kinematics of the moving platform with respect to the fixed base. The re-projection error while doing the calibration in the vision sensor module is 0.10 pixels. Proposed architecture interfaced with the hardware using the PID controller. Encoders are quadrature and have a resolution of 0.15 degrees embedded in the experimental setup to make the system closed-loop (acting as feedback unit).

In this study, the machine-vision technique is employed to measure the angle between two circular holes for the derailleur parts of a bicycle. A delta robot equipped with a motorized zoom lens is constructed as an automatic measurement device. In this way, we can detect the normal vectors of circular holes with different positions and sizes by using only one camera. By calculating the plane normal vectors of two circular holes within the camera coordinate system and performing the cross-product operation, the angle between the two circular holes is obtained. Simulation experiments reveal that the measurement method is influenced by the projection eccentricity error, and the error can be reduced by increasing the focal length and employing the virtual-center alignment method. The results show that the average error for measuring the derailleur parts is approximately 0.061°, and the standard deviation is 0.112°. Experimental analysis indicates that while the magnification of the image is larger, the average error of the measurement result is reduced, and the standard deviation is reduced as well. When the magnification is 0.4×, the measurement average error is 0.04°, and standard deviation is 0.101°. When the distance between the center of the circle and the center of the image is increased, the error in the angle calculation is also increased. A significant improvement is obtained by setting the fitting center position to the optical central position, which omits the influence of the error amplification caused by the distance of the circular hole from the optical axis.

This paper proposes a design of a state estimator for tracking and predicting the object trajectory for the manipulation using a dexterous multi-fingered Delta robot. The observations of the object state acquired from the cameras (Basler), in the real-time scenario. Initially, pixels are removed that corresponds to the background pixels using a mixture of Gaussian algorithms. Secondly, the color invariant approach is implemented as a Hough transform. The same is used for the tracking of the object. This results in the color invariant thresholding to filter the region of interest. As the successive frames have some noise, morphological operations have also performed in to remove if any present outlier. After removing the noise from the frame, estimating the object center followed by velocity estimation done using the k-means clustering. Kalman predictor is used for the prediction of the future state(s) using the current state and known system dynamics. The catching strategy of the object using the Delta robot-based multi-fingered architecture is also discussed. Different trajectories and objects are provided for the catching of the object.

SUMMARYIn brachytherapy, the manual implantation of seeds is not accurate leading to side effects and limiting the use of new procedures. Robotics solutions have to be fully suitable for medical applications especially considering the operating room. This paper investigates a delta robot solution for improving the accuracy of the prostate brachytherapy procedure by proposing a compact and lightweight robot. In addition, the design was thought as a comanipulated robot for a better acceptability and human–machine interaction. The robot kinematics and singularities were determined and the theoretical capability in term of resolution and force feedback was evaluated. A prototype was built in order to experimentally measure the capability of this first prototype.

In this work, a design of a gripper for the underwater OpenROV vehicle is presented. OpenROV is an open-source underwater vehicle design for remote underwater exploration. It can enable systems of underwater internet of things and real-time monitoring. Mechanical aspects of the presented gripper design are discussed including actuation, motion transmission, kinematics and general arrangement, which resembles a delta robot. The Denavit-Hartenberg (DH) notation will be employed to define reference frames on one of the fingers in order to build transformation matrices and the forward kinematics matrix. The results from the forward kinematics are used to define the workspace that can be covered by each finger. The maximum force from the fingertip is estimated using Newton-Euler equations. Finally, the transfer function and the mass moment of inertia of the second link in the finger, that is, the fingertip is calculated for control simulations. A control stability analysis is provided and shows a stable system.

This paper describes the Delta robot design and control method that combines image processing to classify products with the advantage of high speed and accuracy. The Delta robot has three degrees of freedom of paralleled kinetic structure and closed-loop structure. There are three plastic bars, with each bar, one end is connected to the mobile rack via a parallelogram configuration. With such a geometric structure, the end platform is always oriented and only moves forward along the 3 axes of XYZ. Objects to be classified are identified by the camera and then sent to the PC with the coordinates, color, and size of the object. The PC that receives the data will calculate through the dynamic equation combined with image processing to find the coordinates of the real-time object, then send the information to the PLC to control the robot to pick and drop it into the classification box. The system has been installed and tested in reality. The percentage of finding colors and picking the right objects is 97.8%. The Delta Robot control software is programmed with both Auto and Manual modes, simulating the industrial product sorting process.

The delta-robot 3D printer adopts the frame structure of delta-robots. It has three vertical beams which are the supporting parts of the motion and frame mechanism. The pose of the vertical beams is an error source and has the influence on 3D printing precision and printing quality. The effect of such error source on the 3D precision and quality is random and difficult to be captured by measuring instruments. To reveal the mechanism of 3D printing error caused by the pose of vertical beams, through the simulation of parallel motion mechanism and the derivation of non-ideal parallel printing model, the mechanism of error generation and the influence of error source on 3D printing precision are studied. The simulation results show that the tilted vertical beams can indeed cause the 3D printing error and further affect the 3D printing quality, and that the printing error is related to the size and direction of the rotation angles of the vertical beams.

With the advancement of the times, robotics technology is also developing rapidly. Some large enterprises in China use robots to work in manufacturing and handling positions, and also make robots more and more widely used. This paper focuses on the trajectory planning strategy for three-degree-of-freedom high-speed parallel manipulator of Delta robot in Cartesian space under high-speed operation handling, the point-to-point “door” type handling operation trajectory under the condition of ensuring control accuracy and increasing productivity in intelligent packaging is established based on the inverse kinematics model of the manipulator. The 4–3–3-4 degree polynomial interpolation is presented to control height of obstacle avoidance and trajectory length, on this basis, the mapping relationship between the motion features in operation space and those in joint space is established. Taking into account the complexity of trajectory optimization due to multiple constraints, in order to reduce the difficulty of trajectory optimization, it is necessary to ensure smoothness and constrains of angular displacement, angular velocity and angular acceleration of each joint in space, an improved particle swarm optimization algorithm is proposed to optimize trajectory running time of the 4–3–3-4 degree polynomial interpolation. The simulation results by using Matlab indicate that the accurate and stable time-optimal trajectory planning of 4–3–3-4 degree polynomial interpolation can be achieved by means of the improved particle swarm optimization algorithm. Compared with other trajectory planning algorithms, the proposed algorithm is easier to implement, which not only improves the local convergence of particle swarm optimization algorithm, achieves the time optimal trajectory planning of Delta robot, but also realizes the controllability of obstacle avoidance height, therefore which realizes the fast, accurate and safe operation in intelligent packaging.

Purpose Pick-and-place tasks are common across many industrial sectors, and many rigid-linked robots have been proposed for this application. This paper aims to alternatively present the development of a continuum robot for low-load medium-speed pick-and-place tasks. Design/methodology/approach An inversion of a previously proposed dual continuum mechanism, as a key design element, was used to realize the horizontal movements of the CurviPicker’s end effector. A flexible shaft was inserted to realize rotation and translation about a vertical axis. The design concept, kinematics, system descriptions and proof-of-concept experimental characterizations are elaborated. Findings Experimental characterizations show that the CurviPicker can achieve satisfactory accuracy after motion calibration. The CurviPicker is easy to control due to its simple kinematics, while its structural compliance makes it safe to work with, as well as less sensitive to possible target picking position errors to avoid damaging itself or the to-be-picked objects. Research limitations/implications The vertical translation of the CurviPicker is currently realized by moving the flexible shaft. Insertion of the flexible shaft introduces possible disturbances. It is desired to explore other form of variations to use structural deformation to realize the vertical translation. Practical implications The proposed CurviPicker realizes the Schöenflies motions via a simple structure. Such a robot can be used to increase robot presence and automation in small businesses for low-load medium-speed pick-and-place tasks. Originality/value To the best of the authors’ knowledge, the CurviPicker is the first continuum robot designed and constructed for pick-and-place tasks. The originality stems from the concept, kinematics, development and proof-of-concept experimental characterizations of the CurviPicker.

The truss element, due to its simplicity, can fulfill the need to model multibody systems in a way that reduces the size of the problems or improves the efficiency of calculations. The truss element can be used to model rigid and flexible bodies as well as several joints with a single truss element or with aggregates built up from a number of truss elements. With an extended mass description, planar binary rigid links or links that can undergo a uniform dilatation with pin joints can be modelled by a single truss element. Planar ternary elements can likewise be modelled by three truss elements. In three dimensions, a rigid body can be modelled by six truss elements along the edges of a tetrahedron, but also three truss elements can be combined to form a triangular membrane element or six truss elements to form a constant-strain finite solid element. Applications to two benchmark problems and a Delta robot are given.

Traditional parallel-jaw grippers are insufficient for delicate object manipulation due to their stiffness and lack of dexterity. Other dexterous robotic hands often have bulky fingers, rely on complex time-varying cable drives, or are prohibitively expensive. In this paper, we introduce a novel low-cost compliant gripper with two centimeter-scaled 3-DOF delta robots using off-the-shelf linear actuators and 3D-printed soft materials. To model the kinematics of delta robots with soft compliant links, which diverge from typical rigid links, we train neural networks using a perception system. Furthermore, we analyze the delta robot’s force profile by varying the starting position in its workspace and measuring the resulting force from a push action. Finally, we demonstrate the compliance and dexterity of our gripper through six dexterous manipulation tasks involving small and delicate objects. Thus, we present the groundwork for creating modular multi-fingered hands that can execute precise and low-inertia manipulations.

Distributed manipulators - consisting of a set of actuators or robots working cooperatively to achieve a manipulation task - are robust and flexible tools for performing a range of planar manipulation skills. One novel example is the delta array, a distributed manipulator composed of a grid of delta robots, capable of performing dexterous manipulation tasks using strategies incorporating both dynamic and static contact. Hand-designing effective distributed control policies for such a manipulator can be complex and time consuming, given the high-dimensional action space and unfamiliar system dynamics. In this paper, we examine the principles guiding development and control of such a delta array for a planar translation task. We explore policy learning as a robust cooperative control approach, allowing for smooth manipulation of a range of objects, showing improved accuracy and efficiency over baseline human-designed policies.

Primates are the living beings with a greater capacity of manipulation. This skill derives from they have two legs equipped with elements adapted to the manipulation and grasping. The simultaneous use of both legs and arms confer to these living beings their special features to manipulate and manage different objects. As many technical developments inspired when nature laws are observed, parallel robots are conceived in a similar way. In this way, the mechanical structure of a parallel robot is composed by a closed chain in which the end effector is linked to the basis at least by two independent kinematic chains.This definition can be in conflict with the developments about coordinated robots that also constitute closed kinematic chains. Parallel robots simplify these chains in such a way that every one has only one actuator. So, the complexity of the mechanism can be reduced and it is possible to make good use of the energy provided by the actuators to obtain a higher payload capacity or to increase the speed of movement of the end effector. The first theoretical works on mechanical parallel structures appear long time ago, even before the notion of robot. In this way the first parallel mechanism was patented in 1931 (US Patent No 1789680) and was designed by James E. Gwinnett (Gwinnett 1931). In 1940 Willard Pollard presented a robot with 5 degrees of freedom dedicated to painting tasks. The robot was composed of three legs of two links each one. The three actuators of the base drive the position of the tool.However, other more significant parallel mechanisms have been achieved from then. In this way, in 1947 Eric Gough designed the most popular parallel platform. Nowadays numerous platforms can be found with the name of MAST (Multi-Axis Simulation Table). In 1965, Mr. Stewart (Stewart, 1965) described a movement platform of 6 degrees of freedom (dof) designed to use as a flight simulator. On the contrary to the general belief the Stewart mechanism is different to the previously presented by Gough. The work presented by Stewart had and have a great influence in the academic world, and it is considered one of the first works of analysis of parallel structures. At the same time, Klaus Cappel carried out in the Franklin Institute Research Laboratory a lot of researches with parallel platforms of 6 degrees of freedom. In 1967 Cappel patented a motion simulator based on a hexapod (Cappel, 1967). Later, in 1978 Hunt (Hunt 1978) suggested that the mechanisms of the flight simulators can be used as parallel robots. Also Hunt pointed out that parallel robots required a more detailed study in the context of robotic applications due to the advantages of accuracy and rigidity of these platforms.

Thus, a Delta robot maximizes the working speed and the payload that it supports. Thus, in current work, the development and implementation of inverse kinematics in a Delta robot can be observed from different approaches that help to optimize the processing with respect to the equations that govern its motion [4]–[5]. In this way, for the development of the project, as the main design requirements obtained from a task analysis, there is a need for a high speed in the transfer of solid products [6]. Additionally, to guarantee the precision of the mechanism and the parallel calculation of the movement, the embedded NI myRIO system is used, which is a hybrid device from National Instruments, which has a Xilinx Zynq-7010 FPGA and a dual ARM Cortex-A9 processor. Core, designed specifically for the development of complex engineering embedded systems [7].

This article shows the design and construction of a Delta-type parallel robot, based on sizing based on materials science. The document shows the design and optimization process of the Delta robot. First, a method used to search the workspace is presented, subsequently, the structural optimization of the system is explained based on the relationship between structural mass and load mass. Thus, obtaining an optimized structural design capable of supporting the desired loads. Finally, the result of the manufactured robot is observed and a comparison in a discussion section with different works.

Recent advances in robotics, enable the evolution of the manufacturing industry to adapt to the new environments of the industry itself. A distributed deep neural network (DDNN) has been improved in cloud services as a distributed robot control system that can be accessed over protocols such as HTTP, TCP, LwM2M, etc. The conventional deep neural networks (DNN) method has complex computational matrices that will be affected the training accuracy, training runtime, and so on. Microservices-based DNN is deployed to reduce the training workloads of deep neural networks in a single node that can be improved by Containerized DNN architecture. This paper describes a microservices-based for the Deep Neural Network as a Services (DNNaaS) that has been implemented to encourage an inverse kinematic solution of the delta robot control system. Each container trained with non-identical inverse kinematic motions data of delta robot within the data length used is 200 motions data for each node. The proposed method was trained in containers C1 until C4. The training process of containerized DNN performed with accuracy equals to 95.76% and loss equals to 1.06% in containers C1 until C4 for 13.7279 seconds. The proposed method was tested to transmitted 100 IK motions data over Socket.IO with 1.7kB in 336 milliseconds.

In the past decade, parallel manipulators began gaining more and more attention, since they provenly outperform their serial counterparts by several means. The popularity of regular delta robots is especially increasing in high-speed pick and place applications often combined with visual inspection and conveyors. Regular triangle delta robots are well known, and many simulation tools are available in the form of open-source libraries or professional software. Nevertheless, for the recently emerging Generalized Triangle Parallel Robots (GTPR), we lack tools for investigating the geometric and kinematic characteristics. In this paper, we introduce our open-source software tool written in MATLAB for the analysis of the GTPR workspace envelope. The software uses a voxel representation of arbitrary resolution to characterize the robot’s workspace classifying each voxel by the occupation of the represented physical volume. This way, the workspace regions can be investigated from various aspects flexibly regarding the volumetric footprint of the end-effector or any robot parts. Accordingly, the useful workspace and the so-called dead workspace can be evaluated against the specific requirements of a given application.

This paper proposes an iterative learning controller (ILC) under the alignment condition for trajectory tracking of a parallel Delta robot, that performs various repetitive tasks for palletization. Motivated by the high cadence of our application that leads to significant coupling effects, where the traditional PD/PID fail to satisfy the requirements performances. A PD-type ILC is combined with a PD controller in order to enhance the performance through iterations during the whole operation interval. The traditional resetting condition is replaced by the practical alignment condition, then the convergence of the tracking error is derived based on the Lyapunov’s theory. We definitely point out that the position and velocity errors decrease as the number of iterations increases. Experiments are carried out to demonstrate the effectiveness of the proposed controller.

This paper highlights workspace modeling of two parallel robots based on CAD technique. The algorithm is presented and described for the generation of each workspace, which is implemented in CATIA software. The impact of different design parameters on the reachable workspace of DELTA robot manipulator is discussed. Finally, an optimization example is given to show the effectiveness of the proposed approach.

Industrial robotics is a branch of robotics that gained paramount importance in the last century. The presence of robots totally revolutionized the industrial environment in just a few decades. In this paper, a brief history of industrial robotics in the 20th century will be presented, and a proposal for classifying the evolution of industrial robots into four generations is set forward. The characteristics of the robots belonging to each generation are mentioned, and the evolution of their features is described. The most significant milestones of the history of industrial robots, from the 1950’s to the end of the century, are mentioned, together with a description of the most representative industrial robots that were designed and manufactured in those decades.

Purpose Delta robot is a parallel robot specifically designed for high-speed pick and place tasks. However, sometimes they are asked to perform additional assembling and squeezing actions, which is beyond the capability of position-controlled Delta robots. Force sensors may be expensive and add mass to the system. Therefore, the purpose of this paper is to study sensorless force control of Delta robots using limited access interface. Design/methodology/approach Static force analysis is performed to establish a relation between joint torques and external forces. The joint torques are observed from signals provided by motor drivers. A distributed mass model is proposed to compensate the gravity of upper arms and forearms. To minimize the effect of backlash and nonlinear frictions brought by gearboxes, model parameters are calibrated in two separated modes: “LIFTING” and “LOWERING”. Finally, a hybrid force estimation model is built to deal with both cases simultaneously. Surrogate model-based force control law is proposed to increase the force control loop rate and handle the force control problem for discrete position-controlled Delta robots. Findings The results show that the force estimation model is effective and mode separation can significantly improve the accuracy. The force control laws indeed stabilize the robot in desired states. Originality/value The proposed solution is based on position-controlled commercial Delta robot and requires no additional force sensor. It is able to extend Delta robots’ capability and meet requirements of emerging complex tasks.

The article deals with the application of vision guided parallel robot FANUC M-1iA for automated assembly process. Vision system is used for object identification and filtering the data about its position and orientation. Control system based on iR Vision system can process data collected from camera Sony XC-56 fixed to the frame and navigate the end-effector to grasp and move selected objects. Integration of vision guided robot control into the high speed parallel robot can reach high productivity. The functionality of vision guided robot system is demonstrated at automated assembly process of USB memory stick with variable positioning of its components.

Structural flexibility can impact negatively on machine motion control systems by causing unmeasured positioning errors and vibration at locations where accurate motion is important for task execution. To compensate for these effects, command signal prefiltering may be applied. In this paper, a new FIR prefilter design method is described that combines finite-time vibration cancellation with dynamic compensation properties. The time-domain formulation exploits the relation between tracking error and the moment values of the prefilter impulse response function. Optimal design solutions for filters having minimum H2 norm are derived and evaluated. The control approach does not require additional actuation or sensing and can be effective even without complete and accurate models of the machine dynamics. Results from implementation and testing on an experimental high-speed manipulator having a Delta robot architecture with directionally compliant end-effector are presented. The results show the importance of prefilter moment values for tracking performance and confirm that the proposed method can achieve significant reductions in both peak and RMS tracking error, as well as settling time, for complex motion patterns.

Parallel manipulators, also called parallel kinematics machines (PKM), enable robotic solutions for highly dynamic handling and machining applications. The safe and accurate design and control necessitates high-fidelity dynamics models. Such modeling approaches have already been presented for PKM with simple limbs (i.e. each limb is a serial kinematic chain). A systematic modeling approach for PKM with complex limbs (i.e. limbs that possess kinematic loops) was not yet proposed despite the fact that many successful PKM comprise complex limbs. This paper presents a systematic modular approach to the kinematics and dynamics modeling of PKM with complex limbs that are built as serial arrangement of closed loops. The latter are referred to as hybrid limbs, and can be found in almost all PKM with complex limbs, such as the Delta robot. The proposed method generalizes the formulation for PKM with simple limbs by means of local resolution of loop constraints, which is known as constraint embedding in multibody dynamics. The constituent elements of the method are the kinematic and dynamic equations of motions (EOM), and the inverse kinematics solution of the limbs, i.e. the relation of platform motion and the motion of the limbs. While the approach is conceptually independent of the used kinematics and dynamics formulation, a Lie group formulation is employed for deriving the EOM. The frame invariance of the Lie group formulation is used for devising a modular modeling method where the EOM of a representative limb are used to derived the EOM of the limbs of a particular PKM. The PKM topology is exploited in a parallel computation scheme that shall allow for computationally efficient distributed evaluation of the overall EOM of the PKM. Finally, the method is applied to the IRSBot-2 and a 3 R R[2RR]R Delta robot, which is presented in detail.

Currently, there is a need in the industry for design changes to existing installations, such as conveyor lines, various machine tools, 3D printers, and so on. Designing delta robots for 3D printers reveals the advantages of using delta robots as working parts of printers compared to traditional designs. In this article, the direct and inverse problems of the kinematics of the delta robot are solved in a geometric way. Also, dependencies for the search for angular velocities and accelerations of the input links were obtained, which allows in the future to design more accurate working bodies of 3D printers. The research was carried out through mathematical modeling.

The approximation of 3D geometry through single image is a particular instance of 3D reconstruction from several images. The advance information or user input should be provided to retrieve or conclude depth information. This research presents a novel automatic method to enumerated 3D affine measurements from a single perspective image. The least geometric information has been resolute through the image of the scene. The vanishing line and a vanishing point are two required information to reconstruct from an image of a scene. The affine scene structure can be reconstructed through the image of a scene. The proposed approach has many advantages; there is no need of the camera’s intrinsic matrix and the explicit correlation among camera and scene (pose), no need for selecting Vx, Vy, Vz points, novel dexterous robot architecture for manipulation. In this paper, the following approaches have been implemented: (1) the three sets of vanishing points in X, Y, and Z axis; (2) the vanishing lines of the image; (3) distance among planes that parallel to the reference plane; (4) image wrapping; (5) corner detection (algorithm has been implemented in order to make the process automatic). The indigenous data set has been taken for the experiment. The results are compared with Zhang- and ArUco-based calibration. This novel approach has been used to perform tracking and manipulation of an object in real-time environment.

This paper presents path following control for fully actuated rigid body systems in 3-D space. Transverse feedback linearization and a parallel transport frame are used to design a path following controller that is suitable for paths that are parametrized as regular threefold continuously differentiable curves. The application of this frame enables the handling of paths with zero curvature and reduces the complexity of the control law. The path following controller is combined with a compliance control concept. The strategy is verified by a series of measurement results on a DELTA robot with linear drives.

Within this couple of years, a group of skilled people called “Maker” are interested in building everything by themselves. They attempt to develop a small manufacturing environment where allows people to execute a low cost fabrication task. In order to achieve this goal, they utilized flexible and smart manufacturing machines like 3D printers, laser cutter and small CNC. Especially 3D printer, its excellent performances had grasped many government administrators’ attention and developing 3D printing industry has become an important policy of many countries. Some of 3D printing patents have been expired within recent years. This event makes opens sources of 3D printers grow very fast. The Kossel Mini, Rostock and Prusa i3 are the typical examples. All of development kits of the above printers can be freely obtained from the Internet. This event makes a low cost fabrication become possible. However, the quality of their printed parts is dependent on a series of calibrations. The calibrations include defining the dimensions of hard frame of the printer, configuring firmware and setting building parameters of software. In order to let users to go through entire calibrating process, this paper proposed a standard procedure to calibrate Kossel Mini as well as make it print a good quality part.

Future production systems must meet the continual demands for improved productivity and energy efficiency. Being flexible and adaptable, reconfigurable systems offer great opportunities to face these challenges. Against this background, this letter is concerned with the reconfiguration planning of Delta-like parallel robots. Following the trend of equipping the original Delta robot with additional rotational dof, a potential analysis reveals a great variety of dimensional and functional reconfiguration possibilities. Based on this, the reconfiguration planning is optimized applying operations research techniques. In this approach, a fixed number of configurations is optimally selected from the entire configuration space and simultaneously allocated to a set of handling tasks in a most energy efficient way. Each allocation's energy consumption is efficiently computed using Kane's inverse dynamics formulation. The outcome of a case study demonstrates the general applicability and energy-saving potential of the proposed method.

In this paper we put forward the idea of deforming the geometry of a parallel mechanism such that it can operate either as an equivalent rolling robot or quadruped robot. Based on it, we present a novel mobile parallel robot that can change its locomotion modes via different equivalent mechanisms. The robot is in essence a four-arm parallel mechanism in which each arm contains five revolute (R) joints. The axes of the three internal R joints in any arm are parallel and are orthogonal to those of the end joints. Based on singularity and deformation analysis, we show that the upper platform has four practical operation modes, (i.e., translation, planar, rotational, and locked-up modes). Using these operation modes, the robot can realize rolling, tumbling and quadruped locomotion modes by deforming into switching states. The switching configurations of the robot are further identified in which the robot can switch among different locomotion modes, such that the robot can choose its mode to adapt complex terrains. To verify the functionality of the robot, we present the results of a series of simulations, and perform the locomotion modes’ experiments on a manufactured prototype.

More than thirty years after the initial concepts, commercial Delta and Delta-like robots serve a niche market for high-speed pick-and-place applications. Expired patents and new fields of application have led to increased research and innovative designs. By functionally extending the original translational Delta robot with additional serial chains, commercial concepts obtain up to three additional rotational degrees-of-freedom. In this context, the paper in hand is concerned with the analyses of serial-parallel Delta robots with full orientation capabilities. Based on efficient kinematic relations, an energy-related dynamic model is derived for four potential extensions. By solving the inverse dynamic problem, the influences of the additional serial chains on the actuation torques of the basic parallel Delta robot are analyzed. Furthermore, the merits of each individual concept are evaluated using torque-related indices (i.e., energy consumption and root mean square torque) and discussed from a design point of view. It is shown that two types of extensions are predestined for industrial application. In these variants, the wrist motors are either attached to the frame or to the distal links.

The Watt mechanism was invented by James Watt and consisted of a central point of the system that is configured to move as close as possible to a straight line. At one time this Mechanism was used in automobile suspensions as a lateral guiding mechanism, and in the field of robotics, it is used for various robots and in different applications. This article deals with the design and state of the art of new Watt mechanisms, their classification and analysis, their crossed kinematics are analyzed, these efforts represent a first moment to modify the movements of parallel delta-type robots and will allow to increase their precision.

This research aims to develop a prototype of 3-DOF robot that use for pick and place objects with high speed movement and low cost to produce, named parallel robot or delta robot. The robot can approach special applications with fast and smooth control. Thus, it is easy to movement in different positions. It is suitable for transporting workpieces or be able to move in various points. The payload can be up to 500 g. In current application, it can be applied to the food manufacturing industry. Therefore, the robot prototype can be used for food industry companies or related industries field. The project has co-operative from both public sector and private sector. The research and development are conducted by the researchers from the public sector. The private sector provides support materials and equipment. After producing a prototype, the test is carried out by the private sector, evaluates the performance and satisfaction of users to use. When the prototype is completed, the private sector can be commercialized to market in the future.

Resonance selectivity is a new way to achieve “Single-input Multi-output” (SIMO) system via wireless electromagnetic power transmission. But it is limited to low power and open loop systems. This paper presents a new method that uses the principle of resonance selectivity of which system is close loop and the power is over 10w. By using this method, we drive three DC motors to control a delta robot which is based on flexible linkages with feedback control. In this paper, we achieve the position control of delta robot through SIMO and wireless control. This paper introduces the principle of wireless control based on magnetic coupling resonance and the details about control system, and the fabrication and analysis of delta robot based on flexible linkages. According to the results of our experiment, we demonstrate that this method can be applied to control delta robot.

To secure the food supply for future generations it is necessary to increase the automation level in agriculture significantly. One particular problem especially in organic farming is the weeding process. Nowadays the weeding is mostly done by human workers. However this manual weeding is far too expensive and very inhomogeneous. Hence the manual weeding should be replaced by an automated solution. In general a weed control robot system comprises a weed classification and a weed elimination unit. In this paper the development and evaluation of a low-cost delta robot for weed elimination is presented. The performance of the delta robot is illustrated by experimental results.

This paper addresses the design of a 3 degree-of-freedoms (DOF) Delta parallel robot with one DOF redundancy attached to its base. This paper aims at presenting the state-of-the-art of the design and control for the proposed redundant robot for improving time and saving energy consumption. The main idea behind the proposed design consists in examining the performance of a movable Delta robot for pick-and-place purpose. To this end, some improvement has been made on the design of the robot. Spherical magnetic joints are used for the sake of easing the assembling and disassembling of components. At the end, kinematic properties of the robot are investigated.

Delta parallel robot has the advantages of fast motion speed, accurate positioning, low cost and high efficiency. In this paper, OMRON Adapt Hornet 565 3 axis parallel robot is taken as the research object and the control system of Delta robot based on visual tracking technology is studied. The control flow such as camera configuration, model configuration, and process configuration is described in detail, the control system was tested finally. Through the tests, The parallel robot can grasp different shapes of models accurately and quickly under the action of visual tracking.

The main objective of this work is to study the elastic deformations affecting Delta parallel robots during machining operations (e.g., milling). These deformations always induce errors on the programmed tool trajectories. A mathematical evaluation model of these errors has been established. Firstly, this model enables the evaluation of positional errors. Secondly, a compensation procedure of these errors can be performed by instantaneously correcting the motorized joints variables. This procedure is based on the concepts of beam theory involving in particular CASTIGLIANO’s theorem. These deformations (errors) are evaluated at the end effector of the mobile platform. They are estimated as differences between the poses of the end-effector in both hypothesis cases: rigid and flexible. The correction values are obtained by the inverse differential model. The error compensation procedure is performed by an instantaneous correction of the motorized joints variables; the developed approach is applied and exemplified for the Delta parallel robot but remains generalizable to other class of parallel robots.

Mesoscale electromechanical systems find applications in fields such as medical instrumentation, soft robotics, microscopy, flexible electronics and imagining. This paper implements the printed circuit MEMS (PC-MEMS) process [1] for the fabrication of a ‘pop-up’ flexure-based mesoscale system that exploits the simplicity of 2-D manufacturing techniques such as sheet-metal operations and laser cutting to realize a 3-D mechanism. The fabrication of a laminated Delta robot with prismatic actuation is presented to exemplify this process. A working device with actuation and functional components such as linear guides, stepper motors and limit switches is designed and fully realized. Because the mechanism is popped out of the plane to achieve its 3D shape, we present a stiffness analysis to arrive at the out-of-plane (or ‘pop-out’) angles that the planar system must accommodate so that constraints/limits on actuator torque/force can be can satisfied while producing an operational system. The simplicity of the processes makes it a candidate for the use in the emerging open-source hardware technologies for fabricating low-cost, complex, electromechanical systems.

This article describes a sophisticated determination and presentation of a workspace volume for a delta robot, with consideration of its kinematic behavior. With the help of theoretical equations, optimization is performed with the aid of the stiffness and dexterity analysis. Theoretical substructure is coded in Matlab and three-dimensional (3D) data for delta robot are developed in computer-aided design (CAD) environment. In later stages of the project, both 3D and theoretical data are linked together and thus, with the changing design parameter of the robot itself, the Solidworks CAD output adapts and regenerates output with a new set of parameters. To achieve an optimum workspace volume with predefined parameters, a different set of robot parameters are iterated through design optimization in Matlab, and the delta robot design is finalized and illustrated in the 3D CAD environment, Solidworks. This study provides a technical solution to accomplish a generic delta robot with optimized workspace volume.

As demonstrated by the exceptionally successful Delta robot, parallel kinematics Schonflies motion generators (PKSMG) exhibit several advantages over their serial counterparts. Despite its success, the Delta robot suffers from several shortcomings, including a bulky framework and a small workspace-to-footprint ratio. Another drawback is that the kinematic chain generating tool rotation suffers from low torsional stiffness. This letter presents a novel architecture for a nonredundant PKSMG providing infinite tool rotation and an extensive positioning workspace. The workspace and kinematic performance of the proposed architecture are analysed in detail.

This paper presents a system control design on 2 axes “Delta Industrial Robot”. The control system utilizes both the embedded technology and the “Raspberry Pi" which is a low power consumption PC with open source operating system. The user can communicate with the PC and FPGA (Field Programmable Gate Array) via the system GUI interface. The FPGA acts as dedicated hardware to provide both the efficiency and flexibility for the closed-loop servo control system.To calculate all related kinematics equations for the robot, look up table approach has been implemented to reduce the calculation complexity. Python programs are also implemented to create and search the look up tables. The inverse kinematics is the key to find the position of the robot. A test load of 0.2 kg at the velocity of 2.618 m/s, the S.D. of the end effector’s position of the test result is within 0.06 mm.

For general dynamic pick and place tasks that the objects are transferred with high speed by the conveyor belt, the capability of a delta robot to track the traveling objects is very important for the efficiency. To meet the needs of precision and smooth control, a computed-torque control scheme for conveyor tracking is implemented in this paper. For higher efficiency and accuracy, computer vision system, encoder and conveyor belt region are incorporated into the control scheme. Dividing the conveyor belt into three regions, the robot is commanded to track, pick and give up according to the subregions. Conveyor belt is equipped with an encoder that provides the controller with real-time position and speed of the belt. Based upon those informations, the controller automatically compensates the end positions with respect to the belt to adjust for the position of the conveyor. Then, the conveyor tracking problem is converted to a subregional tracking problem.

Hand detection has been the central attention of human-machine interaction in recent researches. In order to track hand accurately, traditional methods mostly involve using machine learning and other available libraries, which requires a lot of computational resource on data collection and processing. This paper presents a method of hand detection and tracking using depth image which can be conveniently and manageably applied in practice without the huge data analysis. This method is based on the two-dimensional matched filter in image processing to precisely locate the hand position through several underlying codes, cooperated with a Delta robot. Compared with other approaches, this method is comprehensible and time-saving, especially for single specific gesture detection and tracking. Additionally, it is friendly-programmed and can be used on variable platforms such as MATLAB and Python. The experiments show that this method can do fast hand tracking and improve accuracy by selecting the proper hand template and can be directly used in the applications of human-machine interaction. In order to evaluate the performance of gesture tracking, a recorded video on depth image model is used to test theoretical design, and a delta parallel robot is used to follow the moving hand by the proposed algorithm, which demonstrates the feasibility in practice.

The following paper describes the design, implementation and experimental results of an Automatic System for Packaging and Quality Control using machine vision in the processed meat industry. The proposed system is composed by a 2-DOF planar robot with vacuum pads to pick and place processed meat packages, a camera sensor to inspect the quality of the packages, a conveyor belt to transport the units to the robot and a linear actuator used to lift the boxes once it has full load. The proposed system picks the packages from the conveyor belt, analyzes them with a computer vision algorithm, separates the defective units and packages the products in good condition. A Graphical User Interface (GUI) is developed for controlling the system and for showing the statistics of the processed meat production, such as the percentage of defective packages, the daily quantity of production, and others. The preliminary experiments and results of the system are presented and discussed.

This paper proposes to attempted is to manipulate an object by a set of three contacts (fingers) i.e. three end effector of the delta robots. As the point of contact with the finger and object changes dynamically, making the problem to have a large degree of variability.This proposal is limited to direct feedback of the object position with respect to the world coordinates and interfacing with the delta robot controlling in real time environment.Detection of markers by three cameras is achieved using ArUco augmented reality library. Experimental results are presented to support the approach in this paper.

This paper deals with kinematic calibration of the Delta robot using distance measurements. The work is mainly placed upon: (1) the error modeling with a goal to classify the source errors affecting both the compensatable and uncompensatable pose accuracy; (2) the full/partial source error identification using a set of distance measurements acquired by a laser tracker; and (3) design of a linearized compensator for real-time error compensation. Experimental results on a prototype show that positioning accuracy of the robot can significantly be improved by the proposed approach.

Recently, delta robots is widely used in many industrial application because the structure of delta robot is close loop chain and have properties of high rigid body and fast movement. However, the moving part of delta robot is arranged in pattern that influenced by gravity and has an impact on control system. In this paper, we proposed force and position control in master-slave configuration while compensate gravity. The control system using disturbance observer (DOB) to estimate sum of action/reaction force and gravity force of master-slave delta robot instead of the force sensors. The external force on travelling plate of delta robot is estimated by disturbance force on upper and computational gravity force from dynamic model. Moreover, the delta robot may various in size due to the conditioning of workspace, therefore the method to control the task space is proposed. The simulation is conduct to verify the control system, compare the position and force of travelling plate with and without gravity compensation.