Design and Development of an FPGA-based Hardware Accelerator for Corner Feature Extraction and Genetic Algorithm-based SLAM System

Simultaneous Localization and Mapping (SLAM) systems are crucial parts of mobile robots. These systems require a large number of computing units, have significant real-time requirements and are also a vital factor which can determine the stability, operability and power consumption of robots. This thesis aims to improve the calculation speed of a lidar-based SLAM system in domestic scenes, reduce the power consumption of the SLAM algorithm, and reduce the overall cost of the whole platform. Lightweight, low-power and parallel optimization of SLAM algorithms are researched. In the thesis, two SLAM systems are designed and developed with a focus on energy-efficient and fast hardware-level design: a geometric method based on corner extraction and a genetic algorithm-based approach. Finally, an FPGA-based hardware accelerated SLAM is implemented and realized, and compared to a software-based system. As for the front-end SLAM system, a method of using a Corner Feature Extraction (CFE) algorithm on FPGA platforms is first proposed to improve the speed of the feature extraction. Considering building a back-end SLAM system with low power consumption, a SLAM system based on genetic algorithm combined with algorithms such as Extended Kalman Filter (EKF) and FastSLAM to reduce the amount of calculation in the SLAM system is also proposed. Finally, the thesis also proposes and implements an adaptive feature map which can replace a grid point map to reduce the amount of calculation and utilization of hardware resources. In this thesis, the lidar SLAM system with front-end and back-end parts mentioned above is implemented on the Xilinx PYNQ Z2 Platform. The implementation is operated on a mobile robot prototype and evaluated in real scenes. Compared with the implementation on the Raspberry Pi 3B+, the implementation in this thesis can save 86.25% of power consumption. The lidar SLAM system only takes 20 ms for location calculation in each scan which is 5.31 times faster compared with the software implementation with EKF

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

Advanced photonic and electronic systems - WILGA 2017

WILGA annual symposium on advanced photonic and electronic systems has been organized by young scientist for young scientists since two decades. It traditionally gathers more than 350 young researchers and their tutors. Ph.D students and graduates present their recent achievements during well attended oral sessions. Wilga is a very good digest of Ph.D. works carried out at technical universities in electronics and photonics, as well as information sciences throughout Poland and some neighboring countries. Publishing patronage over Wilga keep Elektronika technical journal by SEP, IJET by PAN and Proceedings of SPIE. The latter world editorial series publishes annually more than 200 papers from Wilga. Wilga 2017 was the XL edition of this meeting. The following topical tracks were distinguished: photonics, electronics, information technologies and system research. The article is a digest of some chosen works presented during Wilga 2017 symposium. WILGA 2017 works were published in Proc. SPIE vol.10445

An embedded adaptive optics real time controller

The design and realisation of a low cost, high speed control system for adaptive optics (AO) is presented. This control system is built around a field programmable gate array (FPGA). FPGA devices represent a fundamentally different approach to implementing control systems than conventional central processing units. The performance of the FPGA control system is demonstrated in a specifically constructed laboratory AO experiment where closed loop AO correction is shown. An alternative application of the control system is demonstrated in the field of optical tweezing, where it is used to study the motion dynamics of particles trapped within laser foci

A Review of Hybrid Battery Management System (H-BMS) for EV

Significant to a major pollution contributor in passenger vehicles, electric vehicles are more acceptable to use on the road. Electric Vehicles (EVs) burn energy based on the usage of the battery. The usage of the battery in EVs is monitored and controlled by Battery Management System (BMS). A few factors monitor and control Battery Management System (BMS). This paper reviewed the battery charging technology and Remote Terminal Unit (RTU) development as a Hybrid Battery Management System (H-BMS) for Electric Vehicle (EV)

Convergence of Intelligent Data Acquisition and Advanced Computing Systems

This book is a collection of published articles from the Sensors Special Issue on "Convergence of Intelligent Data Acquisition and Advanced Computing Systems". It includes extended versions of the conference contributions from the 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS’2019), Metz, France, as well as external contributions