Abul Bashar Raz’s Post

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Robotics Voice | Resource sharing | Emerging Technology | Advance Research | Automation | Robotics and AI

Real-time trajectory planning for autonomous driving harnesses the strengths of Gaussian Processes (GP) and Incremental Refinement to navigate dynamic environments safely and efficiently. Gaussian Processes offer a probabilistic framework for modeling uncertainties in vehicle dynamics and environmental conditions, ensuring that the planned trajectories are smooth and have a high confidence level. This is crucial for maintaining safety and comfort during autonomous driving. Incremental Refinement complements this by providing a mechanism to iteratively improve the trajectory in real-time, adapting to new data and environmental changes as they occur. This iterative process allows for continuous adjustments, ensuring that the vehicle can respond promptly to unexpected obstacles or alterations in the driving scenario. By integrating the probabilistic modeling capabilities of GPs with the adaptive nature of Incremental Refinement, autonomous driving systems can achieve a high degree of reliability and responsiveness, essential for real-world operation. The video is for the paper “Real-Time Trajectory Planning for Autonomous Driving with Gaussian Process and Incremental Refinement”, accepted by ICRA2022. Authors: Jie Cheng, Yingbing Chen, Qingwen Zhang u Gan and Ming Liu Paper: https://lnkd.in/gGD3ktmy Github: https://lnkd.in/gT2DSZ25 #autonomusdriving #algorithm #ros #carla #robotics

Zacck Osiemo

Transforming Real-Time Systems: Expert RTOS Consulting from Assessment to Production.

4mo

Maybe it’s me but it seems like every cool thing is signal processing… 

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Gowtham Singh Saud

Artificial intelligence🤖, Machine learning , Data science, Cloud ☁️

4mo

great work !!!

Reza Khadem hovize

Laboratory and research expert at Iran University of Science and Technology

4mo

Insightful!

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