Cartesian control of redundant robots

A Cartesian-space position/force controller is presented for redundant robots. The proposed control structure partitions the control problem into a nonredundant position/force trajectory tracking problem and a redundant mapping problem between Cartesian control input F is a set member of the set R(sup m) and robot actuator torque T is a set member of the set R(sup n) (for redundant robots, m is less than n). The underdetermined nature of the F yields T map is exploited so that the robot redundancy is utilized to improve the dynamic response of the robot. This dynamically optimal F yields T map is implemented locally (in time) so that it is computationally efficient for on-line control; however, it is shown that the map possesses globally optimal characteristics. Additionally, it is demonstrated that the dynamically optimal F yields T map can be modified so that the robot redundancy is used to simultaneously improve the dynamic response and realize any specified kinematic performance objective (e.g., manipulability maximization or obstacle avoidance). Computer simulation results are given for a four degree of freedom planar redundant robot under Cartesian control, and demonstrate that position/force trajectory tracking and effective redundancy utilization can be achieved simultaneously with the proposed controller

Master assisted cooperative control of human and robot

A cooperative control approach between human and robot takes an important role to carry out various tasks in hazardous environments or space. In this case, a robot is operated based on the cooperation between direct human control and autonomous robot control. In this study, a neural network is introduced for cooperating process between human control and robot control in order to optimize the degree of cooperation of human and robot. The degree of participation of human operator into the control is determined based on a reference cooperative model which expresses desired human and robot cooperative form. The experiment has executed the contacting tasks for the various object walls using a two-degrees of freedom Cartesian robot. The results indicate the availability of the proposed cooperating method for the cooperative control of human and robot </p

The KALI multi-arm robot programming and control environment

The KALI distributed robot programming and control environment is described within the context of its use in the Jet Propulsion Laboratory (JPL) telerobot project. The purpose of KALI is to provide a flexible robot programming and control environment for coordinated multi-arm robots. Flexibility, both in hardware configuration and software, is desired so that it can be easily modified to test various concepts in robot programming and control, e.g., multi-arm control, force control, sensor integration, teleoperation, and shared control. In the programming environment, user programs written in the C programming language describe trajectories for multiple coordinated manipulators with the aid of KALI function libraries. A system of multiple coordinated manipulators is considered within the programming environment as one motion system. The user plans the trajectory of one controlled Cartesian frame associated with a motion system and describes the positions of the manipulators with respect to that frame. Smooth Cartesian trajectories are achieved through a blending of successive path segments. The manipulator and load dynamics are considered during trajectory generation so that given interface force limits are not exceeded

How to Deploy a Wire with a Robotic Platform: Learning from Human Visual Demonstrations

In this paper, we address the problem of deploying a wire along a specific path selected by an unskilled user. The robot has to learn the selected path and pass a wire through the peg table by using the same tool. The main contribution regards the hybrid use of Cartesian positions provided by a learning procedure and joint positions obtained by inverse kinematics and motion planning. Some constraints are introduced to deal with non-rigid material without breaks or knots. We took into account a series of metrics to evaluate the robot learning capabilities, all of them over performed the targets

Robot Cartesian 3 Sumbu (X,Y,Z) Untuk Aplikasi Pengambilan dan Penempatan Benda Kerja

Labiartorium Otomasi Program Studi Teknik Elektronika Politeknik Manufaktur Negeri Bangka Belitung (Polman Babel), sejak didirikannya telah difasilitasi dengan sebuah robot cartesian merk Festo, Namun, robot ini hanya memiliki 2 sumbu (X,Y) dan tidak dapat beroperasi lagi dikarenakan kedua sensor jarak sumbu X,Y dan kontrol PLC yang digunakannya mengalami kerusakan. Untuk itu, perlu dilakukan tindakan perbaikan terhadap robot. Perbaikan robot dimaksudkan untuk mengoperasikan kembali robot cartesian tersebut sebagai bahan ajar praktikum. Agar pemanfaatannya dapat lebih maksimal untuk para mahasiswa, pada robot yang diperbaiki dilakukan modifikasi dengan tujuan agar robot dapat berkgerak secara 3 sumbu(X,Y,Z) untuk melakukan aplikasi pengambilan dan penempatan benda kerja. Adapaun peralatan yang dibutuhkan untuk modifikasi tersebut antara lain menggunakan sebuah double acting cylinder sebagai sumbu z, dengan vacuum gripper pada ujungnya untuk mencekam benda kerja, 2 buah reed switches sebagai sensor sumbu z, 3 buah sensor benda kerja, yaitu sensor optik, sensor kapasitif, dan sensor induktif, untuk proses pemilihan benda kerja agar dapar ditempatkan sesuai stasiunnya masing-masing. Untuk konrtol PLC diganti dengan IC Mikrokontroler ATMega 16L, menggunakan bahasa pemrograman CodeVisionAVR. Begitu juga sensor jarak sumbu X, Y diganti dengan sensor sumbu yang baru. Sebagai hasil pengujian dengan metode On-Off yang dilakukan, didapat bahwa robot dapat melakukan fungsi aplikasi pengambilan dan penempatan benda sesuai stasiunnya masing-masing dengan baik walaupun untuk posisi koordinat yang dicapai masih terdapat error dengan kisaran +1-+3(mm) untuk sumbu X dan +3 - +5 (mm) untuk sumbu

Real-time computation of distance to dynamic obstacles with multiple depth sensors

We present an efficient method to evaluate distances between dynamic obstacles and a number of points of interests (e.g., placed on the links of a robot) when using multiple depth cameras. A depth-space oriented discretization of the Cartesian space is introduced that represents at best the workspace monitored by a depth camera, including occluded points. A depth grid map can be initialized off line from the arrangement of the multiple depth cameras, and its peculiar search characteristics allows fusing on line the information given by the multiple sensors in a very simple and fast way. The real-time performance of the proposed approach is shown by means of collision avoidance experiments where two Kinect sensors monitor a human-robot coexistence task

Real-time cartesian force feedback control of a teleoperated robot

Active cartesian force control of a teleoperated robot is investigated. An economical microcomputer based control method was tested. Limitations are discussed and methods of performance improvement suggested. To demonstrate the performance of this technique, a preliminary test was performed with success. A general purpose bilateral force reflecting hand controller is currently being constructed based on this control method

Geometry-aware Manipulability Learning, Tracking and Transfer

Body posture influences human and robots performance in manipulation tasks, as appropriate poses facilitate motion or force exertion along different axes. In robotics, manipulability ellipsoids arise as a powerful descriptor to analyze, control and design the robot dexterity as a function of the articulatory joint configuration. This descriptor can be designed according to different task requirements, such as tracking a desired position or apply a specific force. In this context, this paper presents a novel \emph{manipulability transfer} framework, a method that allows robots to learn and reproduce manipulability ellipsoids from expert demonstrations. The proposed learning scheme is built on a tensor-based formulation of a Gaussian mixture model that takes into account that manipulability ellipsoids lie on the manifold of symmetric positive definite matrices. Learning is coupled with a geometry-aware tracking controller allowing robots to follow a desired profile of manipulability ellipsoids. Extensive evaluations in simulation with redundant manipulators, a robotic hand and humanoids agents, as well as an experiment with two real dual-arm systems validate the feasibility of the approach.Comment: Accepted for publication in the Intl. Journal of Robotics Research (IJRR). Website: https://sites.google.com/view/manipulability. Code: https://github.com/NoemieJaquier/Manipulability. 24 pages, 20 figures, 3 tables, 4 appendice

A Depth Space Approach for Evaluating Distance to Objects -- with Application to Human-Robot Collision Avoidance

We present a novel approach to estimate the distance between a generic point in the Cartesian space and objects detected with a depth sensor. This information is crucial in many robotic applications, e.g., for collision avoidance, contact point identification, and augmented reality. The key idea is to perform all distance evaluations directly in the depth space. This allows distance estimation by considering also the frustum generated by the pixel on the depth image, which takes into account both the pixel size and the occluded points. Different techniques to aggregate distance data coming from multiple object points are proposed. We compare the Depth space approach with the commonly used Cartesian space or Configuration space approaches, showing that the presented method provides better results and faster execution times. An application to human-robot collision avoidance using a KUKA LWR IV robot and a Microsoft Kinect sensor illustrates the effectiveness of the approach

Compliance error compensation in robotic-based milling

The paper deals with the problem of compliance errors compensation in robotic-based milling. Contrary to previous works that assume that the forces/torques generated by the manufacturing process are constant, the interaction between the milling tool and the workpiece is modeled in details. It takes into account the tool geometry, the number of teeth, the feed rate, the spindle rotation speed and the properties of the material to be processed. Due to high level of the disturbing forces/torques, the developed compensation technique is based on the non-linear stiffness model that allows us to modify the target trajectory taking into account nonlinearities and to avoid the chattering effect. Illustrative example is presented that deals with robotic-based milling of aluminum alloy