scholarly journals A Novel Design and Implementation of Autonomous Robotic Car Based on ROS in Indoor Scenario

Robotics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 19
Author(s):  
Chunmei Liu ◽  
Chengmin Zhou ◽  
Wen Cao ◽  
Fei Li ◽  
Pengfei Jia
Keyword(s):  
Autonomous Vehicle ◽  
Indoor Navigation ◽  
Operation System ◽  
Environmental Friendliness ◽  
Design And Implementation ◽  
Detection And Tracking ◽  
Localization And Mapping ◽  
New Energy ◽  
Software Modules ◽  
Novel Design

Pervasive deployment of autonomous vehicle all over the world is an undisputed trend in the future. Autonomous vehicle will inevitably play an essential role in decreasing traffic jams, reducing threats from driving while intoxicated (DWI), and assisting the handicapped to get around. At the same time, the new energy vehicles (NEV) especially the electromobile is gradually adopted by several governments like Germany, USA and China as compulsive transportation tools from the standpoint of environmental friendliness. Taking these two crucial trends into consideration, this article proposes a scheme of autonomous robotic car based on robot operation system (ROS) in electromobile-like car which can be easily transplanted to commercial electromobile. In this article, the design and implementation of robotic car are demonstrated in detail which involves overall architecture of functional modules, hardware design, obstacle avoidance, localization and mapping, land detection and tracking, velocity control and indoor navigation. All software modules and hardware are integrated in NVIDIA Jetson TX1 and TRAXXAS car.

Smartphone-Based Indoor Visual Navigation with Leader-Follower Mode

2021 ◽  
Vol 17 (2) ◽  
pp. 1-22
Author(s):  
Jingao Xu ◽  
Erqun Dong ◽  
Qiang Ma ◽  
Chenshu Wu ◽  
Zheng Yang
Keyword(s):  
Real Time ◽  
Environmental Changes ◽  
State Of The Art ◽  
Visual Navigation ◽  
Indoor Navigation ◽  
Location Services ◽  
Localization And Mapping ◽  
Leaders And Followers ◽  
Indoor Navigation System ◽  
Free Pair

Existing indoor navigation solutions usually require pre-deployed comprehensive location services with precise indoor maps and, more importantly, all rely on dedicatedly installed or existing infrastructure. In this article, we present Pair-Navi, an infrastructure-free indoor navigation system that circumvents all these requirements by reusing a previous traveler’s (i.e., leader) trace experience to navigate future users (i.e., followers) in a Peer-to-Peer mode. Our system leverages the advances of visual simultaneous localization and mapping ( SLAM ) on commercial smartphones. Visual SLAM systems, however, are vulnerable to environmental dynamics in the precision and robustness and involve intensive computation that prohibits real-time applications. To combat environmental changes, we propose to cull non-rigid contexts and keep only the static and rigid contents in use. To enable real-time navigation on mobiles, we decouple and reorganize the highly coupled SLAM modules for leaders and followers. We implement Pair-Navi on commodity smartphones and validate its performance in three diverse buildings and two standard datasets (TUM and KITTI). Our results show that Pair-Navi achieves an immediate navigation success rate of 98.6%, which maintains as 83.4% even after 2 weeks since the leaders’ traces were collected, outperforming the state-of-the-art solutions by >50%. Being truly infrastructure-free, Pair-Navi sheds lights on practical indoor navigations for mobile users.

scholarly journals Performance Analysis of NDT-based Graph SLAM for Autonomous Vehicle in Diverse Typical Driving Scenarios of Hong Kong

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3928 ◽  
Author(s):  
Weisong Wen ◽  
Li-Ta Hsu ◽  
Guohao Zhang
Keyword(s):  
New York ◽  
Hong Kong ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Tall Buildings ◽  
Point Clouds ◽  
Reliability Estimation ◽  
Traffic Condition ◽  
Localization And Mapping ◽  
Graph Slam

Robust and lane-level positioning is essential for autonomous vehicles. As an irreplaceable sensor, Light detection and ranging (LiDAR) can provide continuous and high-frequency pose estimation by means of mapping, on condition that enough environment features are available. The error of mapping can accumulate over time. Therefore, LiDAR is usually integrated with other sensors. In diverse urban scenarios, the environment feature availability relies heavily on the traffic (moving and static objects) and the degree of urbanization. Common LiDAR-based simultaneous localization and mapping (SLAM) demonstrations tend to be studied in light traffic and less urbanized area. However, its performance can be severely challenged in deep urbanized cities, such as Hong Kong, Tokyo, and New York with dense traffic and tall buildings. This paper proposes to analyze the performance of standalone NDT-based graph SLAM and its reliability estimation in diverse urban scenarios to further evaluate the relationship between the performance of LiDAR-based SLAM and scenario conditions. The normal distribution transform (NDT) is employed to calculate the transformation between frames of point clouds. Then, the LiDAR odometry is performed based on the calculated continuous transformation. The state-of-the-art graph-based optimization is used to integrate the LiDAR odometry measurements to implement optimization. The 3D building models are generated and the definition of the degree of urbanization based on Skyplot is proposed. Experiments are implemented in different scenarios with different degrees of urbanization and traffic conditions. The results show that the performance of the LiDAR-based SLAM using NDT is strongly related to the traffic condition and degree of urbanization. The best performance is achieved in the sparse area with normal traffic and the worse performance is obtained in dense urban area with 3D positioning error (summation of horizontal and vertical) gradients of 0.024 m/s and 0.189 m/s, respectively. The analyzed results can be a comprehensive benchmark for evaluating the performance of standalone NDT-based graph SLAM in diverse scenarios which is significant for multi-sensor fusion of autonomous vehicle.

scholarly journals An Enhanced FPGA Based Asynchronous Microprocessor Design Using VIVADO and ISIM

2018 ◽  
Vol 7 (2) ◽  
pp. 199-208
Author(s):  
Archana Rani ◽  
Naresh Grover
Keyword(s):  
The Novel ◽  
Design And Implementation ◽  
Microprocessor Design ◽  
Novel Design

This paper deals with the novel design and implementation of asynchronous microprocessor by using HDL on Vivado tool wherein it has the capability of handling even I-Type, R-Type and Jump instructions with multiplier instruction packet. Moreover, it uses separate memory for instructions and data read-write that can be changed at any time. The complete design has been synthesized and simulated using Vivado. The complete design is targeted on Xilinx Virtex-7 FPGA. This paper more focuses on the use of Vivado Tool for advanced FPGA device. By using Vivado we get enhaced analysis result for better view of properly Route Placed design.

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