FPGA-Based Fused Smart Sensor for Dynamic and Vibration Parameter Extraction in Industrial Robot Links

Intelligent robotics demands the integration of smart sensors that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require a constant monitoring of several parameters such as motion dynamics, inclination, and vibration. This work presents a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. The proposed smart sensor implements a new methodology based on an oversampling technique, averaging decimation filters, FIR filters, finite differences and linear interpolation to estimate the interest parameters, which are computed online utilizing digital hardware signal processing based on field programmable gate arrays (FPGA)

Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots

Flexible manipulator robots have a wide industrial application. Robot performance requires sensing its position and orientation adequately, known as forward kinematics. Commercially available, motion controllers use high-resolution optical encoders to sense the position of each joint which cannot detect some mechanical deformations that decrease the accuracy of the robot position and orientation. To overcome those problems, several sensor fusion methods have been proposed but at expenses of high-computational load, which avoids the online measurement of the joint’s angular position and the online forward kinematics estimation. The contribution of this work is to propose a fused smart sensor network to estimate the forward kinematics of an industrial robot. The developed smart processor uses Kalman filters to filter and to fuse the information of the sensor network. Two primary sensors are used: an optical encoder, and a 3-axis accelerometer. In order to obtain the position and orientation of each joint online a field-programmable gate array (FPGA) is used in the hardware implementation taking advantage of the parallel computation capabilities and reconfigurability of this device. With the aim of evaluating the smart sensor network performance, three real-operation-oriented paths are executed and monitored in a 6-degree of freedom robot

Impedance control of a dual-arm robot.

Intensive research efforts are currently directed toward special robotic applications. One of the largest international projects with a focus on this research is the Space Station Freedom. Canada's contribution to this project is a Mobile Servicing System (MSS). This system will be used for assembly and maintenance of the space station. The MSS will consist of a long single arm with a dual-arm robot attached to its end. They require a hierarchical controller to coordinate the arms while executing such tasks as trajectory generation, arm-arm collision avoidance, arm-obstacle collision avoidance, and the manipulation of solid and flexible body payloads. This thesis presents the research work for building a functional hardware and software model of a test-bed dual-arm robot with flexible object handling capabilities using impedance control. It addresses issues such as input-output linearization, perturbation observer, sensor fusion, and provides the experimental results of a dual-arm manipulator using the proposed techniques. To date, no work exists which shows that the application of a dual-arm robot handling flexible payloads in space applications is possible