Autonomous Emergency Breaking (AEB) Evaluation For Indian Traffic Scenarios using GPS and LiDAR Data

Autonomous emergency braking (AEB) and forward-collision warning (FCW) is a cutting-edge active safety technology that assists drivers in avoiding or minimizing crashes with global cars and other vulnerable road users (VRU) for SAE autonomy Level 3 and 4 categories. The Indian traffic scenario data is recorded for Hyderabad city using Lidar and GPS sensors. This dataset is available at IIIT Hyderabad. This real-world traffic scenario is converted into a virtual closed-loop scenario for evaluating AEB and FCW for different VRUs in this present study. The synthetic Radar and camera data are generated by the radar detection generator and vision detection generator blocks in the driving scenario simulator. The results of the virtual scenario developed using sensor perception reveals the ego car velocity ego car acceleration when the lead vehicle's time-to-collision (TTC) is less than FCW. The simulation results are observed for a total of 9 seconds. The control algorithms for AEB and FCW prevent accidents with rear-end collisions of global vehicles, and accurate world traffic scenario data assessed its performance. © 2022 IEEE

Future Mobility with eVTOL Personal Air Vehicle (PAV): Urban Air Mobility (UAM) Concept

Many countries consider Urban Air Mobility (UAM) a new mode of transportation for intra-regional short-distance journeys. The system is one of the upcoming on-demand airborne transportation networks and includes drone taxis and personal air vehicles. The primary purpose of the UAM concept is to use electric vertical take-off and landing (eVTOL) vehicles to identify passenger locations, fly and cruise, load the passengers, and deliver them to their destinations. UAM system is a currently evolving field, and multiple concepts such as multi-copter concepts, Lift and Cruise concepts, and Tilt-Wing concepts are being proposed. The behavior of each concept vehicle, and hence its energy efficiency, varies. Using low-altitude airspace, UAM is intended to provide an innovative transportation model for passengers and goods in metropolitan areas with significantly increased mobility. Ground infrastructure incorporating vertiports, regulations, policies, and other vital components, is required to transform UAM from design to operation. Electric flight is thought to be the next step toward more environmentally sustainable air travel. In the present study, a personal air vehicle (PAV) based eVTOL concept is proposed for UAM. The preliminary design and modelling of PAV are discussed here. The aerodynamic performance of propeller characteristics used in PAV design is compared using numerical and experimental studies. The results show that at different velocities, the normal and side forces generated by the propellers are found to be more stable in PAV cruise mode/ forward flight mode, respectively. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd

Autonomous Bio-Inspired Micro Aerial Vehicle (MAV)

The usage and development of Unmanned Aerial Vehicles (UAVs) have increased rapidly in agriculture, health care, and the military. Based on the weight, UAVs are classified as Nano, Micro, Small, Medium, and Large Aerial Vehicles. More precisely, Nano, Micro, and small UAVs are widely used for the defence applications such as Intelligence, Surveillance, and Reconnaissance. Micro Aerial Vehicles (MAVs), which come under a weight less than or equal to 2kg, are preferable for Surveillance applications. Due to the lightweight and flapping effect, the autonomous flight of MAVs is a significant challenge in robotics. An autonomous MAV includes independent operations like take-off, cruising, and landing. Among all these operations, landing is the most crucial one. Maintaining the constant speed and glide path is a challenging task for a MAV during the landing. Also, it has to predict the exact point of landing within less time. An autonomous Bio-inspired flapping wing MAV is designed and developed for military rescue operations. This MAV consists of two flapping wings with a supporting chassis subjected to sustain hovering, maneuverability, and more efficient forwarding flight. Aerial bird is considered as the inspiration for the designed model. This paper proposed a bio-inspired MAV using a Pixhawk flight controller for autonomous navigation and conducted preliminary experiments on the prototype MAV. The overall expected outcome of the current effort is to generate a simplified independent Bio-Inspired functioning MAV model with an efficient mechanical and electrical system. © 2022 IEEE

Mobile Robot Terrain Mapping for Path Planning using Karto Slam and Gmapping Technique

Mapping is one of the mobile robot's most basic applications. A mobile robot's sensors, such as a laser sensor, sonar, and camera, are used to create the map. Most mapping techniques use simultaneous localization and Mapping (SLAM). SLAM allows for creating a map and the localization of the robot's position on it. This research compares the trajectories of a mobile robot created by several ROS-based SLAM systems. And also, GMapping and Karto SLAM are two well-known SLAM algorithms employed. The mobile robot is equipped with 2D lidar and monocular camera. The mapping is done at two distinct locations, in labs of varying sizes with varying numbers of static and dynamic objects. Three test runs are conducted for GMapping to examine the effects of various variables on mapping quality, including particle filter, mapping delay, and robot speed. The results show a significant difference in operation completion time and mapping accuracy as a result of the parameter changing over the three test runs. Due to the improved accuracy of the parameter used in the second test run of GMapping and Karto SLAM, the accuracy of the maps is the basis for this improvement. On the other hand, the second test run with robot particle filter 30, mapping delay 1, and speed 0.13m/s is thought to be the best3\2 13Q/0. © 2022 IEEE