SGA Recruitment (India) LLP的动态

Embotech collaborates with Outsight and Hesai Technology to power Automated Vehicle Marshalling (AVM) systems. ??? Together, we’re enabling fully autonomous vehicle movements within BMW Group production facilities, using state-of-the-art LiDAR and perception technology to set new standards in efficiency and safety. ???????? ?????? ???????? ??????????: ?? [???????? ???? ?????? ???????? ?????????? ?????????????? ???? ?????? ????????????????] Exciting developments ahead—stay tuned! #AutomatedVehicleMarshalling #autonomousvehicles #automateddriving

SERDP & ESTCP is collaborating with Central Florida Tech Grove to enhance wildfire response capabilities by evaluating and deploying advanced remotely operated equipment and ground-based autonomous vehicles. This initiative focuses on technologies (excluding aircraft) designed for hazardous wildfire conditions. A hybrid tabletop exchange event is scheduled for January 24, 2025, from 1 PM to 4 PM EST, offering an opportunity to learn more and engage with this effort.?

In this paper, the authors investigate various glare reduction techniques, including the proposed saturated pixel-aware glare reduction technique for improved performance of the #computer #vision (#CV) tasks employed by the perception layer of #autonomous #vehicles (#AVs). They evaluate these glare reduction methods based on various performance metrics of the CV algorithms used by the perception layer. Specifically, the authors considered object detection, object recognition, object tracking, depth estimation, and lane detection which are crucial for autonomous driving. ---- Zeeshan Kaleem, Sousso Kelouwani More details can be found at this link: https://lnkd.in/e_TmNY_u

AutoCarROS [1] contains the ROS 2 variant of the AutoCarROS [2] repository. It is a template for the development of a robust non-holonomic autonomous vehicle platform in a simulated environment using ROS 2 and Gazebo 11. - launches Contains the main launch files for quick launching - autocar_description Contains the model's URDF and RViz configuration files - autocar_gazebo Contains the world files and model's SDF - autocar_map Contains the Bayesian Occupancy Filter stack - autocar_msgs Contains all custom messages used throughout every package - autocar_nav Contains the navigation stack This project is using Gazebo classic and ROS 2 Foxy. It might require some love to update it. Good palce to contribute! #ros #ros2 #simulation #gazebo #opensource #nonholomic #autonomousvehicle #navigation #autonomousdriving [1] https://lnkd.in/dMTKHJAv [2] https://lnkd.in/dg3db9wk

Thrilled to announce the publication of our paper titled “Uncertainty-Aware DRL for Autonomous Vehicle Crowd Navigation in Shared Space” in IEEE Transactions on Intelligent Vehicles! In this work, we present a novel reinforcement learning-based social navigation algorithm for autonomous vehicles. This algorithm tackles the challenge of uncertain pedestrian behavior by incorporating prediction uncertainty into the decision-making process. Our proposed integrated prediction and planning approach promotes safe and farsighted navigation in crowded environments. We achieve this through a novel reward function that encourages minimizing collision probability over a predicted time horizon. Experimental results in a realistic pedestrian trajectory simulation demonstrate the effectiveness of our model, showcasing superior performance in collision avoidance, respecting personal space, and generating human-like trajectories for autonomous vehicles. Huge thanks to my supervisors and co-authors Dr. Nasser L. Azad, Dr. Kerstin Dautenhahn, and Dr. Moojan Ghafurian for their invaluable support throughout this project! Want to learn more? Access the full paper here: https://lnkd.in/gHWXdxVX Dive deeper into the code on GitHub: https://lnkd.in/gTUXydPu Feel free to reach out if you have any questions or would like to discuss the details further. #autonomousdriving #reinforcementlearning #IEEE

Our paper "Improved Adaptive High-Order Sliding Mode-Based Control for Trajectory Tracking of Autonomous Underwater Vehicles", has just been published in IEEE Journal of Oceanic Engineering.

SERDP is partnering with Central Florida Tech Grove to conduct a comprehensive #technology scan and subsequent prize challenge focused on evaluating and deploying advanced remotely operated equipment, ground-based autonomous vehicles, and other remote-operated technologies (excluding aircraft) for use in #wildfire response, particularly in hazardous conditions. Learn more and register for our hybrid tabletop exchange event on January 24: https://lnkd.in/g6mdAU2Z

Another piece of evidence shows that if the future of transport is connected, it can be safely automated! Our latest research explores the safety benefits of cooperative messages in automated vehicles, focusing on navigating road work zones. You can find further details in our new article published in IEEE Transactions on Intelligent Vehicles. Thanks to the team, especially Muhammad Hussain, and our funders for their support. #TransportInnovation #AutomatedVehicles #RoadSafety #ConnectedVehicles #TransportFutures

-----CAV or AV----- The mobility and safety benefits of Connected and Automated vehicles (CAVs) are an ongoing area of research. While several studies demonstrate the advantages of CAVs, there remains a gap in quantifying these benefits over conventional Automated Vehicles (AVs). In a recent article in IEEE Transactions on Intelligent Vehicles co-authored by Muhammad Hussain, Sebastien Glaser, Gregoire Larue, Sepehr G. Dehkordi and Mahmoud Masoud, we evaluated the safety and mobility benefits of CAVs over AVs in Roadworks (RW) conditions, which is a challenging driving environment. By using state-of-the-art models such as Minimising Overall Braking Induced by Lane Changes (MOBIL); and Intelligent Driver Model (IDM), we explored the effectiveness of CAVs over AVs. Details of this study can be found in the following early access article. https://lnkd.in/gtFUXfT5 We are thankful to iMOVE Australia, and Department of Transport and Main Roads, Queensland, Australia for the funding of this project. The authors would also like to gratefully acknowledge Amit Trivedi and Merle Wood for the review and fruitful suggestions in improving this research. Western Australian Centre for Road Safety Research, University of Western Australia UWA School of Psychological Science ?CARRS-Q The University of Western Australia QUT (Queensland University of Technology) University of the Sunshine Coast King Fahd University of Petroleum & Minerals - KFUPM

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