Mateusz Saków

Self-sensing teleoperation system based on 1-dof pneumatic manipulator

Paper presents a novel approach to a control design of bilateral teleoperation systems with force-feedback. The problem statement, analysis of research achievements to date, and the scope of the study are presented. The new design of a control unit for a master-slave system with force-feedback is presented on a simple and ideal 1-DOF bilateral teleoperation system. System control unit was based on an inverse model. The model was used to reduce value of force in the force-feedback communication channel, that the system might generate in freemotion. A substantial part of the paper is focused on the development of a mathematical model covering phenomena occurring in the investigated control scheme. The new approach was validated on a test-stand of a rotating non-linear pneumatic manipulator arm. Two linear pneumatic actuators were used in the drive system. The paper presents the modeling procedure of the experimental setup and the model used in the study. Three experiments are described to demonstrate the new control approach to master-slave objects with force-feedback. The paper contains conclusions regarding the control system and the experimental setup.

Unilateral Hydraulic Telemanipulation System for Operation in Machining Work Area

The paper is focused on the minimization of the time transport delay effect which is present in the communication channel of a telemanipulation system. For the minimization of the time transport delay, a prediction block was proposed. The prediction block is characterized by a unitary gain and positive-linear phase shift in a useful frequency spectrum of the system operation. These features allow the block to predict the signal with a constant time and minimizes the gain to a unity level. The use of prediction blocks in the communication channel strongly improved the position tracking abilities of the unilateral system which feature was confirmed in experiments.

Nonlinear inverse modeling with signal prediction in bilateral teleoperation with force-feedback

In the paper a sensor-less control scheme for a bilateral teleoperation system with a force-feedback based on a prediction of an input and an output of a non-linear inverse model by prediction blocks is presented. The prediction method was designed to minimize the effect of the transport delay and the phase shift of sensors, actuators and mechanical objects. The solution is an alternative to complex non-linear models like artificial neural networks which requires complex stability analysis and control systems with high computing power. The effectiveness of the method has been verified on the hydraulic manipulator test stand.

Loader Crane Working Area Monitoring System Based on LIDAR Scanner

Segmentation and analysis of the environment using 3D data (point clouds) in real time are dynamically developing the area. Falling prices of depth sensors based on technologies: LIDAR, ToF, RADAR, increasing computing power, growing interest in autonomous vehicles and robots, favor this trend. This paper presents test studies of loader crane working area monitoring system based on the Velodyne VLP-16 LIDAR scanner. Developed system use ground plane estimation and surroundings segmentation algorithms. The ground points filtering algorithm is based on the dot product of vectors as well as interpolation using the RANSAC method. Segmentation algorithm uses angle threshold between points and breadth-first search (BFS) method for determine neighborhood. The proposed system was adapted to operate with sparse LIDAR data in real time. Described system allows for detects human bodies, environmental elements, and monitors changes in the loader crane work area. The effectiveness of developed algorithms was tested on data obtained from loader crane test bench. An experiment showed that segmentation and monitoring loader crane working area in real time even with sparse data is possible. Moreover, the authors discuss other methods used to segmentation sparse point cloud in real time, describe the Velodyne VLP-16 scanner, and presents an outline of current research into HMI interfaces for loader cranes.

Ground plane estimation from sparse LIDAR data for loader crane sensor fusion system

Research on the development of control systems for loader cranes, despite their importance in the industry, is conducted by only a few scientific centers. West Pomeranian University of Technology, Szczecin in collaboration with loader cranes manufacturer — Cargotec company, started research on the multisensory monitoring system for cranes. proposed system also allows you to track the position of the operator. This paper presents the subsystem for ground plane estimation and ground points filtration. The developed algorithm uses data from the Velo dyne LIDAR VLP-16 scanner. The subsystem is designed for real time operation. It is based on the RANSAC algorithm and vector dot product. The effectiveness of the algorithm was compared with other algorithms described in this publication. Tests were carried out on a loader crane test bench at various positions of the LIDAR sensor. Experiments confirms that ground plane estimation results of the proposed algorithm are better than other presented methods.

Real-time ground filtration method for a loader crane environment monitoring system using sparse LIDAR data

The segmentation and analysis of the environment using three-dimensional (3D) data (point clouds) is a dynamically developing area. This article presents a real-time ground filtration method for the loader crane environment monitoring system. The falling prices of depth sensors based on light detection and ranging (LIDAR), time of flight (ToF), radio detection and ranging (RADAR) technologies, and growth-computing power led us to use the Velodyne VLP-16 sensor in the developed system. In the presented filtering solution, we use characteristic scan pattern properties, the dot product of vectors, and interpolation using the RANSAC method. Algorithm performance was evaluated based on real data acquired under different conditions, and the results were compared to known filtration methods. The described algorithm is developed for real-time operation; therefore, the computation time is critical. Furthermore, in this article, we discuss other methods used to extract ground points from the entire point cloud in real time, describe Velodyne VLP-16 scanner and data acquisition methods.

Real-Time and Low Phase Shift Noisy Signal Differential Estimation Dedicated to Teleoperation Systems

The paper contains a description of a real-time differentiation algorithm dedicated to teleoperation systems. The algorithm is based on the least squares polynomial approximation method and it is a modified version of a local and nearest neighbors samples based approach. The algorithm fits a defined polynomial to an asymmetric data set. In this case, the nearest neighbor samples are only taken from the one side of the filtered vector of a signal samples. This feature allowed to reduce the value of the phase shift, especially for a low frequency spectrum, where man-machine control interfaces are usually operating. The strong reduction of a phase shift allowed to minimize the variable time delay of the estimated signal differential according to a measured control signal.

Signal Prediction in Bilateral Teleoperation with Force-Feedback

In the paper a sensor-less and self-sensing control scheme for a bilateral teleoperation system with force-feedback based on a prediction of an input of a non-linear inverse model by prediction blocks was presented. As a part of the paper a method of a time constant estimation of the prediction block was also proposed. The prediction method of an input of an inverse model was designed to minimize the effect of the transport delay and the phase shift of sensors, actuators and mechanical objects. The solution is an alternative to complex non-linear models like NARX or artificial neural networks, which requires complex stability analysis, and control systems with high computing powers. The effectiveness of the method has been verified on the hydraulic manipulator’s test stand.

The use of machine vision to control the basic functions of a CNC machine tool using gestures

Abstract This paper presents a concept of a vision system which can simplify the way in which some basic functions of CNC machines can be controlled. The proposed system enables the operator to control a machine tool using gestures. The developed solution is based on Microsoft Kinect for a Windows v2 sensor with a time-of-flight camera. A gesture recognition module was implemented in the VC 760 milling machine with an open control system (O.C.E.A.N.). To conduct tests of the proposed interface, a set of gestures used to control a CNC machine was developed. Furthermore, the concept, the structure of the system and the test results are discussed. In summary, the advantages and potential problems of the proposed control system and plans for future development are discussed.