Robotic Arm System Research Articles

Robust Tracking and Vibration Suppression for a Two-Inertia System by Combining Backstepping Approach With Disturbance Observer

In this paper, we consider the problem of designing a robust controller for a two-inertia system which contains arbitrarily large (but bounded) model uncertainties and disturbances. The research is motivated by the fact that a two-inertia system represents most of an industrial robot arm system that has a flexible joint, for which vibration suppression and robust control against model uncertainties and external disturbances are very important. The proposed controller consists of two parts: the outer-loop controller designed by the backstepping approach and the inner-loop controller by the new <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">partial</i> disturbance observer (DOB). The DOB is responsible for compensating the input-matched uncertainties and disturbances, while the backstepping controller is designed for dealing with the rest. The proposed controller makes tracking error and vibration of the system suppressed within an arbitrarily small bound during operation time when full states are measured. The results are verified by simulations and experiments with a Luenberger observer.

Load transportation by dual arm robot using sliding mode control

In this study, a sliding mode controlled dual arm robotic system was designed. Such multi-arm, collaborative and synchronous robots typically are employed in hazardous situations such as radioactive materials transport explosives disposal and industrial applications. In the present study, a high performance, robust, non-chattering sliding mode controller (SMC) was developed for the purpose of safe load handling, transportation and trajectory realization. First, dynamic equations of robot/load interaction were derived. Then, the robust SMC was designed for the dual arm robotic system. In order to test the robustness of the proposed SMC, parameter variations and external disturbances were introduced to the system. Furthermore, for comparative purposes, the conventional and widely used, PID controller was also applied to the dual arm robot. Significantly, it was found that the SMC made smaller trajectory tracking errors than the PID controller. An overall analysis of the numerical results confirmed that the dual-arm robotic systems with the proposed SMC can safely and effectively be used in hazardous applications.

Online tuning gain scheduling MIMO neural PID control of the 2-axes pneumatic artificial muscle (PAM) robot arm

This paper presents a detailed study to investigate the possibility of applying the online tuning gain scheduling MIMO neural dynamic DNN-PID control architecture to a nonlinear 2-axes pneumatic artificial muscle (PAM) robot arm so as to improve its joint angle position output performance. The proposed controller was implemented as a subsystem to control the real-time 2-axes PAM robot-arm system so as to control precisely the joint angle position of the 2-axes PAM robot arm when subjected to system internal interactions and load variations. The results of the experiment have demonstrated the feasibility and benefits of the novel proposed control approach in comparison with the traditional PID control strategy. The proposed gain scheduling neural MIMO DNN-PID control scheme forced both joint angle outputs of 2-axes PAM robot arm to track those of the reference simultaneously under changes of the load and system coupled internal interactions. The performance of this novel proposed controller was found to be outperforming in comparison with conventional PID. These results can be applied to control other highly nonlinear systems.

2A1-F06 双腕五指ロボットハンド制御システムの開発 : 作業記述システムの改善とシミュレータの導入

We developed a general Dual Five-Fingered Robotic Hand Arm system and a simple robot task programming system named SAEN preparing for the manpower shortage on the nursing side and the welfare side in the future. SAEN did not have enough abilities for advanced works because it was difficult for SAEN to describe error avoidances and synchronization of plural threads. So, in this research, we introduced an exception handling and the synchronization mechanism as solutions of those problems. And, we developed SAEN simulator by using ODE (Open Dynamics Engine) for debugging of SAEN program. It was shown that both of our new features of SAEN work fine and improve the effectiveness of SAEN programming through of simulation experiments and investigation of SAEN program source codes.

Design of a Robust Controller for Position Control of a Small One-Link Robot Arm with Input Time-Delay

This paper deals with a robust controller design problem for a small one-link robot arm system subject to input time delay and load variations. The uncertain parameters of the system are considered as a disturbance input. A disturbance observer(DOB) has been designed to alleviate disturbance effects and to compensate performance degradation owing to the time-delay. This paper employs a new DOB structure for non-minimum phase systems together with the Smith predictor. We propose a new controller for reducing the both effects of disturbance and time-delay. In order to test the performance of proposed controller, four different other control laws are compared with the proposed one by computer simulations. The simulation results show the effectiveness of the proposed control method.

空気圧人工筋による人に対して安全な多自由度ロボットアーム技術の開発

Robotic systems intended for domestic housekeeping or elderly care tasks will have interaction with humans and therefore demand an intrinsically safe design. Conventional robotic systems are driven by heavy, high power and high stiffness electric motors, making them unsafe for human coexistence. To overcome this problem, we have developed a robotic arm system using pneumatic muscle actuators, which is intrinsically safe given its low weight and pliant structure. In this paper we present the design of the robot arm and associated control system, showing that the robot has positioning and force control accuracy sufficient for daily domestic tasks.

Low-cost teleoperable robotic arm

A low-cost robotic arm and controller system is presented. The controller is a desktop model of the robotic arm with the same degrees of freedom whose joints are equipped with sensors. Manipulating the controller by hand causes the robotic arm to mimic the movement in master–slave fashion. This is accomplished simply and at low-cost by taking advantage of widely available hobby radio control components. The system uses the trainer (“Buddy Box”) function available on common radio control transmitters as a simple interface between microcontroller and transmitter. The microcontroller produces a time-division multiplexed signal comprising three channels in proportional pulse modulated (PPM) format. The arm design could be used for various light-duty applications and this paper describes a version fitted with a video camera. The arm prototype is designed for an under-vehicle inspection robot. In this application, the video camera mounted on the robotic arm allows inspection of difficult-to-view locations under vehicles. The master–slave operator interface provides an easy-to-learn method for robotic arm manipulation.

Learning to reach by reinforcement learning using a receptive field based function approximation approach with continuous actions

Reinforcement learning methods can be used in robotics applications especially for specific target-oriented problems, for example the reward-based recalibration of goal directed actions. To this end still relatively large and continuous state-action spaces need to be efficiently handled. The goal of this paper is, thus, to develop a novel, rather simple method which uses reinforcement learning with function approximation in conjunction with different reward-strategies for solving such problems. For the testing of our method, we use a four degree-of-freedom reaching problem in 3D-space simulated by a two-joint robot arm system with two DOF each. Function approximation is based on 4D, overlapping kernels (receptive fields) and the state-action space contains about 10,000 of these. Different types of reward structures are being compared, for example, reward-on- touching-only against reward-on-approach. Furthermore, forbidden joint configurations are punished. A continuous action space is used. In spite of a rather large number of states and the continuous action space these reward/punishment strategies allow the system to find a good solution usually within about 20 trials. The efficiency of our method demonstrated in this test scenario suggests that it might be possible to use it on a real robot for problems where mixed rewards can be defined in situations where other types of learning might be difficult.

1A2-D05 油圧駆動型双腕ロボットアームシステムの開発 : 次世代知能化建機の研究・開発用プラットフォーム

1A2-D05 油圧駆動型双腕ロボットアームシステムの開発 : 次世代知能化建機の研究・開発用プラットフォーム

Implementation of Humanoid Robot Arm Based on SERCOS Network

Designing, implementing and evaluating the performance of a humanoid robot arm, we verified its applicability and effectiveness based on the Serial Real-Time Communication System (SERCOS), which follows the concept of modularization corresponding to projected research. We also proposed single joint design modular for humanoid robot arm systems.

POSITION CONTROL FOR FLIXEBLE JOINT MANIPULATOR USING ARTIFICIAL NEURAL Network

The control of a rotating single flexible link manipulator and/or a two-coupled flexible link manipulator arm is a highly nonlinear problem. Due to the distributed flexibility. The Mechanical system of a flexible joint two-degree manipulator robot arm has been designed and implemented by using stepper motor, movement axis and External Model Circuit (EMC) for controller. The (EMC) includes Buffer, stepper motor driver and programmable Input/Output. This system is controlled by using two method .The first is Artificial Neural Networks (ANN). The neural network has a feed-forward topology and learning algorithm used Back-Propagation. The second is direct method to supply the program with co-ordinates as positioning data for initializing the robot arm.

The Kinetostatic Conditioning of Two-Limb Schönflies Motion Generators

This paper introduces a study on the kinetostatic conditioning of two-limb Schönflies motion generators. These are robots capable of producing the motions undergone by the end-effector of what is known as selective-compliance assembly robot arm (SCARA) systems, which can best be described as the motions of the tray of a waiter: three independent translations plus one rotation about an axis of fixed orientation. SCARA systems are usually understood as four-axis serial robots, Schönflies motion generators being a generalization thereof, that encompass first and foremost parallel architectures. Kinetostatic conditioning is understood here in connection with the condition number of each of the two Jacobian matrices of the parallel robot under study. After a brief introduction on the geometry and the kinematics of two-limb parallel systems, the kinetostatics of this class of robots is discussed; whence, the calculation of the kinetostatic conditioning of these robots is undertaken. The motivation behind this work is the need to understand an unstable behavior of the prototype in a substantial part of its workspace, which is attributed to poor conditioning. A main result of this paper is the correlation between the shortest dimension of the robot kinematic chain and the characteristic length, which hints to the need of specifying the range of the characteristic length when optimizing the dimensions of robots of the class studied here, a result that may equally hold for parallel robots in general.

On Designing Fuzzy Controllers for a Class of Nonlinear Networked Control Systems

This paper is concerned with controller design for a class of nonlinear networked control systems. These systems are approximated by uncertain linear networked Takagi-Sugeno (T-S) models with both network-induced delay and data packet dropout. Sufficient conditions are derived for the existence of a fuzzy controllers. Then, an iterative algorithm for the controller design is proposed. A control problem of a flexible-joint robot arm system is studied to show the effectiveness of the iterative algorithm.

Robotic sample manipulation for stress and texture determination on neutron and synchrotron X-ray diffractometers

In this paper we report on a new robotic arm system for fast, accurate and flexible sample manipulation for stress and texture analysis in geometrically complex engineering components on neutron and synchrotron X-ray diffractometers. A Staeubli serial six-axis robotic arm offering full six degrees of freedom for sample movement, with a spatial positioning accuracy of the order of tens of microns has been commissioned. Reverse engineering and 3D visualization techniques are employed to control the sample manipulation procedure. Two basic applications of the system, one for stress measurements using synchrotron X-ray diffraction using the sin 2 ψ inclination method, and one for pole figure determination for texture analysis using neutron diffraction, are presented. The former required measurements at eight angles for each measurement location; the latter a full quadrant of solid angle with the centre of the sample maintained stationary. With new robotic arms being produced with higher payloads (the current one is limited to 9 kg), but similar positional uncertainties, robotic sample manipulation offers very flexible measurement strategies for complex geometries, without the need for repeated manual intervention for sample reorientation.

Nonlinear robust fault reconstruction and estimation using a sliding mode observer

This paper considers fault detection and estimation issues for a class of nonlinear systems with uncertainty, using an equivalent output error injection approach. A particular design of sliding mode observer is presented for which the parameters can be obtained using LMI techniques. A fault estimation approach is presented to estimate the fault and the estimation error is dependent on the bounds on the uncertainty. For a special class of uncertainty, a fault reconstruction scheme is presented where the reconstructed signal can approximate the fault signal to any accuracy. The proposed fault estimation/reconstruction signals are only based on the available plant input/ouput information and can be calculated on-line. Finally, a simulation study on a robotic arm system is presented to show the effectiveness of the scheme.

Optimizing robotic part feeder throughput with queueing theory

Purpose – This paper aims to study a commercially available industrial part feeder that uses an industrial robot arm and computer vision system. Three conveyor belts are arranged to singulate and circulate parts, bringing them under a camera where their pose is recognized and subsequently manipulated by the robot arm. The problem is addressed of optimizing belt speeds and hence throughput of this feeder that avoid: starvation, where no parts are visible to the camera and saturation, where too many parts prevent part pose detection or grasping.Design/methodology/approach – Models are developed for intermittent and continuous motion feeding based on a 2D Poisson process. Renewal theory is applied to model intermittent motion and an M/G/1 queue with customer impatience to model continuous motion feeding. These models are verified using discrete event simulation.Findings – The models predict and optimize feeder behaviour very accurately and it is possible to compute optimal settings for different part sizes a...

An automated robot arm system for small animal tissue biopsy under dual-image modality

The ability to non-invasively monitor cell biology in vivo is one of the most important goals of molecular imaging. Imaging procedures could be inter-subject performed repeatedly at different investigating stages; thereby need not sacrifice small animals during the entire study period. Thus, the ultimate goal of this study was to design a stereotactic image-guided system for small animals and integrated it with an automatic robot arm for in vivo tissue biopsy analysis. The system was composed of three main parts, including one small animal stereotactic frame, one imaging-fusion software and an automatic robot arm system. The system has been thoroughly evaluated with three components; the robot position accuracy was 0.05±0.02 mm, the image registration accuracy was 0.37±0.18 mm and the system integration was satisfactorily within 1.20±0.39 mm of error. From these results, the system demonstrated sufficient accuracy to guide the micro-injector from the planned delivery routes into practice. The entire system accuracy was limited by the image fusion and orientation procedures, due to its nature of the blurred PET imaging obtained from the small objects. The primary improvement is to acquire as higher resolution as possible the fused imaging for localizing the targets in the future.

School-based use of a robotic arm system by children with disabilities

A robotic arm system was developed for use by children who had very severe motor disabilities and varying levels of cognitive and language skills. The children used the robot in a three-task sequence routine to dig objects from a tub of dry macaroni. The robotic system was used in the child's school for 12-15 sessions over a period of four weeks. Goal attainment scaling indicated improvement in all children in operational competence of the robot, and varying levels of gain in functional skill development with the robot and in carryover to the classroom from the robot experiments. Teacher interviews revealed gains in classroom participation, expressive language (vocalizations, symbolic communication), and a high degree of interest by the children in the robot tasks. The teachers also recommended that the robot should have more color, contrast and character, as well as generating sounds and/or music for student cues. They also felt that the robotic system accuracy should be increased so that teacher assistance is not necessary to complete the task.

A minimally invasive biomechatronic approach for breast cancer surgery

This paper presents a novel mechatronic approach for minimally invasive excision of breast tumors along with a pre-defined margin tissue, by extending directional vacuum-assisted biopsy (DVAB) technique. Means of overcoming the limitations of mammotome biopsy probe (by J&J) while adopting it for complete removal of tumor and margin area, which may lead to unpredictable removal of tissue from ill-defined location, are presented. A dual arm robotic system in a hybrid configuration, whereby imaging probe and excision needle can be independently maneuvered, is designed using a modular approach. Two systematic methods for tissue excision viz. the progressive removal and oscillatory removal are proposed and implemented for multiple resections through the target tissue region and ensuring complete removal of the tumor. Collapsing of the tissue after each removal has been taken into consideration while developing the systematic method of tissue removal. System GUI is developed to help the end-users/clinicians for image guidance, target and margin demarcation, on-line update on volume estimation, positioning and controlling the manipulator. A representative number of tissue phantoms were tested to validate the feasibility of the system and proposed concept. The accuracy and repeatability of our present system was measured as ± 0.5 mm and within ± 0.1 mm, respectively.

Development of Intelligent McKibben Actuator (1st Report, Realization of Position Servo System by Soft Displacement Sensor)

This study aims at development of Intelligent McKibben actuator, in which micro displacement/pressure sensors and micro valves are integrated. In this first report, development of rubber displacement sensor and its application to servo system using McKibben actuator are reported. Recently McKibben actuator attracts engineers because of light weight, high output power and high compliance. But in case of servo control using it, the systems need encoders or potentiometers, so the systems tend to grow in size and to take away from compliance at present. To solve thus problems, soft rubber sensor was developed, which was made of rubber covered its surface with conductive resin thinly. Electrical resistance of rubber sensor changes in response to extending motion of the rubber. We built the rubber sensor into McKibben actuator and named it Intelligent McKibben actuator. Servo system using single Intelligent McKibben actuator was realized, and tested. Furthermore, we fabricated a robot arm system configured by two Intelligent McKibben actuators. Experimental results showed that the actuator has good potential for realizing polymer made intelligent actuator.