For the past decade, the main problem that has attracted researchers’ attention in aerial robotics is the position estimation or Simultaneous Localization and Mapping (SLAM) of Unmanned Aerial Vehicles (UAVs) where the GPS signal is poor or denied. This article reviews the strengths and weaknesses of existing methods in the field of aerial robotics. There are many different techniques and algorithms that are used to overcome the localization and mapping problem of these UAVs. These techniques and algorithms use different sensors, such as Red Green Blue-Depth (RGB_D), Light Detecting and Ranging (LIDAR), and Ultra-wideband (UWB). The most common technique is used, i.e., probability-based SLAM, which uses two algorithms: Linear Kalman Filter (LKF) and Extended Kalman Filter (EKF). LKF consists of five phases and this algorithm is just used for linear system problems. However, the EKF algorithm is used for non-linear systems. Aerial robots are used to perform many tasks, such as rescue, transportation, search, control, monitoring, and different military operations because of their vast top view. These properties are increasing their demand as compared to human service. In this paper, different techniques for the localization of aerial vehicles are discussed in terms of advantages and disadvantages, practicality and efficiency. This paper enables future researchers to find the suitable SLAM solution based on their problems; either the researcher is dealing with a linear problem or a non-linear problem.

This paper presents a high speed On-Off Keying (OOK) modulator using local oscillator (LO) cancellation technique. Implemented in 28 nm bulk CMOS process, a 100 GHz modulator post layout full-wave EM simulation results are executed for data-rate up to 50 Gbps. The modulator has on-off isolation of 21.6 dB. The proposed modulator design consumes power up to 9.6 mW and occupies chip area of 0.025 mm 2 .

In this age, the automotive surveillance service is a well-known proven product implemented in conventional transport systems and widely known vehicle entities worldwide. It is a system that can be very robust and reliable. Through this work, GPS (Global Positioning System is implemented, which is used to locate and identify any automobile. This concept is an integrated device that can steadily track a speeding object and communicate the device’s status whenever its identification is required. It must obtain the NodeMCU (ESP8066 module) for the network connection device, which is routinely connected to the GPS device and the Arduino board through which it functions. The NodeMCU is used to relay the device’s status simultaneously from a distant location. The context of the application, “Bus Management System”, which is designed in MIT, provided an android studio for researchers to design any application interface. The network interface could be reviewed on the accounts-receivable public network in the form of charts. The program shows responses to the mobile application; it only requires logging in with a data network. The application, “Bus Management System”, displays the sensor values in terms of GPS coordinates statistics. This IoT based transport assistive system is cost effective and less complex from other existing IoT based transport assistive system.