Noncollocated proprioceptive sensing for lightweight flexible robotic manipulators

This article presents the design of a noncollocated feedback system for flexible serial manipulators. The device is a passive serial chain of encoders and lightweight links, mounted in parallel with the manipulator. This measuring arm effectively decouples the manipulator's proprioception from its actuators by providing information on the actual end effector pose, accounting for both joint and link flexibility. The kinematic redundancy of the measuring chain allows for safe operation in the context of human–robot interaction. A simple yet effective error model is introduced to assess the suitability of the proposed sensor system in the context of robotic control. The practicality of the device is first demonstrated by building a physical joint-encoder assembly and a simplified planar measuring arm prototype. With this additional feedback, a task-space position controller is devised and tested in simulation. Finally, the simulation results are validated with an experimental 3-DoF lightweight manipulator prototype equipped with a five-joint measuring arm

A gantry robot automatic positioning system using computational vision

Este trabalho foi financiado pelo Concurso Anual para Projetos de Investigação, Desenvolvimento, Inovação e Criação Artística (IDI&CA) 2016 do Instituto Politécnico de Lisboa. Código de referência IPL/2017/ROBOTCLEAN/ISELWith the new industrial revolution (industry 4.0) under way, there is a need to automate/digitalize even the simplest processes to keep companies competitive, efficient and secure. This work proposes an automatic and robotic positioning system with position control through the image of video cameras. The objective is to propose this type of automatic system to companies aiming to improve robotic systems operations that are often controlled manually and with associated risks. The developed system was tested in simulation (using Matlab) and in an experimental scale prototype.info:eu-repo/semantics/publishedVersio

Sistema de posicionamento robotizado segundo o conceito da indúsria 4.0

Trabalho final de mestrado para obtenção do grau de mestre em Engenharia MecânicaCom a evolução da automação industrial, existe a necessidade de automatizar até os processos mais simples, de forma a manter as empresas industriais competitivas. O objectivo deste Trabalho Final de Mestrado é automatizar o processo de posicionamento do sistema de lavagem interior dos tanques dos camiões-cisterna, com supervisão a partir da Internet. Neste trabalho de projecto desenvolveu-se um sistema de posicionamento robotizado com controlo de posição através da imagem de câmaras de vídeo. O algoritmo de visão foi programado no software Matlab com auxílio de bibliotecas de visão computacional e de comunicação com um controlador de motores de passo desenvolvido em arquitectura de Arduino. O desenvolvimento foi feito dentro do conceito da indústria 4.0, ou seja, todo o sistema é totalmente automático com excepção da introdução do número de bocas pelo operador. Foram testados controladores com comunicação à base do protocolo Ethernet, nomeadamente o PC com o cliente do Matlab a comunicar com um servidor Apache para que seja possível estabelecer a conexão entre o sistema e a supervisão na Internet. Todo o sistema pode ser supervisionado através de um smartphone ou tablet a partir do browser instalado. Construiu-se também um protótipo à escala, seleccionado de modo a validar o algoritmo de visão e as simulações efectuadas em Matlab. O protótipo é constituído por uma estrutura em perfis V-slot, motores de passo, o controlador e câmara USB, que embora tenha uma menor qualidade de imagem, foi suficiente para validar o algoritmo de visão implementado.With the evolution of industrial automation, there is a need to automate even the simplest processes, to keep industrial companies competitive. The objective of this Master’s Thesis is to automate the positioning system of an internal washing process of tanker trucks, with supervision from the Web. In this project work, a robot positioning system was developed with position control through the image of video cameras. The vision algorithm was programmed in Matlab software with the help of computer vision toolboxes and communication with a stepper motor controller developed in Arduino architecture. The development was done within the concept of the industry 4.0, that is, the whole system is totally automatic except for the introduction of the number of holes by the operator. Controllers were tested with communication based on the Ethernet protocol, namely the PC with the Matlab client to communicate with an Apache server so that it is possible to establish the connection between the system and the supervision on the web. The entire system can be supervised through a smartphone or tablet from the installed browser. A prototype was also built to scale, selected to validate the vision algorithm and the simulations performed in Matlab. The prototype consists of a structure in V-slot profiles, as well as the controller and USB camera that although having a lower quality of image, was enough to validate the implemented vision algorithm.N/

Fusion of low-cost and light-weight sensor system for mobile flexible manipulator

There is a need for non-industrial robots such as in homecare and eldercare. Light-weight mobile robots preferred as compared to conventional fixed based robots as the former is safe, portable, convenient and economical to implement. Sensor system for light-weight mobile flexible manipulator is studied in this research. A mobile flexible link manipulator (MFLM) contributes to high amount of vibrations at the tip, giving rise to inaccurate position estimations. In a control system, there inevitably exists a lag between the sensor feedback and the controller. Consequently, it contributed to instable control of the MFLM. Hence, there it is a need to predict the tip trajectory of the MFLM. Fusion of low cost sensors is studied to enhance prediction accuracy at the MFLM’s tip. A digital camera and an accelerometer are used predict tip of the MFLM. The main disadvantage of camera is the delayed feedback due to the slow data rate and long processing time, while accelerometer composes cumulative errors. Wheel encoder and webcam are used for position estimation of the mobile platform. The strengths and limitations of each sensor were compared. To solve the above problem, model based predictive sensor systems have been investigated for used on the mobile flexible link manipulator using the selected sensors. Mathematical models were being developed for modeling the reaction of the mobile platform and flexible manipulator when subjected to a series of input voltages and loads. The model-based Kalman filter fusion prediction algorithm was developed, which gave reasonability good predictions of the vibrations of the tip of flexible manipulator on the mobile platform. To facilitate evaluation of the novel predictive system, a mobile platform was fabricated, where the flexible manipulator and the sensors are mounted onto the platform. Straight path motions were performed for the experimental tests. The results showed that predictive algorithm with modelled input to the Extended Kalman filter have best prediction to the tip vibration of the MFLM