Emergency obstacle avoidance trajectory planning method of intelligent vehicles based on improved hybrid A
G Chen, J Yao, Z Gao, Z Gao, X Zhao, N Xu… - SAE International Journal …, 2023 - sae.org
In this article, we present a spatiotemporal trajectory planning algorithm for emergency
obstacle avoidance. Utilizing obstacle and driving environment data from the sensing …
obstacle avoidance. Utilizing obstacle and driving environment data from the sensing …
Distributionally robust risk map for learning-based motion planning and control: A semidefinite programming approach
In this article, we propose a novel safety specification tool, called the distributionally robust
risk map (DR-risk map), for a mobile robot operating in a learning-enabled environment …
risk map (DR-risk map), for a mobile robot operating in a learning-enabled environment …
A collaborative path planning method for mobile cable-driven parallel robots in a constrained environment with considering kinematic stability
J Xu, BG Kim, KS Park - Complex & Intelligent Systems, 2023 - Springer
Mobile cable-driven parallel robot (MCDPR) is a variant of cable-driven parallel robots
(CDPRs) by mounting several mobile bases to replace the conventional fixed frame. The …
(CDPRs) by mounting several mobile bases to replace the conventional fixed frame. The …
State estimation and localization based on sensor fusion for autonomous robots in indoor environment
M Doumbia, X Cheng - Computers, 2020 - mdpi.com
Currently, almost all robot state estimation and localization systems are based on the
Kalman filter (KF) and its derived methods, in particular the unscented Kalman filter (UKF) …
Kalman filter (KF) and its derived methods, in particular the unscented Kalman filter (UKF) …
Path Planning of a Mobile Robot Based on the Improved Rapidly Exploring Random Trees Star Algorithm
J Wang, E Zheng - Electronics, 2024 - mdpi.com
With the increasing utilization of sampling-based path planning methods in the field of
mobile robots, the RRT* algorithm faces challenges in complex indoor scenes, including …
mobile robots, the RRT* algorithm faces challenges in complex indoor scenes, including …
Adaptive sampling-based moving obstacle avoidance for cable-driven parallel robots
J Xu, C Qian, JW Park, KS Park - IEEE/ASME Transactions on …, 2022 - ieeexplore.ieee.org
The ability to avoid the moving obstacle is critical to cable-driven parallel robots (CDPRs)
operating in real-world environments. However, the moving obstacle raises extraordinary …
operating in real-world environments. However, the moving obstacle raises extraordinary …
Multi-risk Aware Trajectory Planning for Car-like Robot in Highly Dynamic Environments
M Chen, J Liu, J Pang, Z Jian, P Chen… - 2023 IEEE 26th …, 2023 - ieeexplore.ieee.org
Safe trajectory planning in highly dynamic environments remains a substantial challenge.
Traditional risk-based trajectory planning algorithms solve planning problems in …
Traditional risk-based trajectory planning algorithms solve planning problems in …
Learn to efficiently exploit cost maps by combining RRT* with Reinforcement Learning
Safe autonomous navigation of robots in complex and cluttered environments is a crucial
task and is still an open challenge even in 2D environments. Being able to efficiently …
task and is still an open challenge even in 2D environments. Being able to efficiently …
What feels light to you? An exploration into supplying simple information through a light bar in a highly automated vehicle
As advanced features integrate into vehicle, drivers may feel apprehensive to use them.
Providing users information using human-machine interfaces (HMIs) may ease fears; …
Providing users information using human-machine interfaces (HMIs) may ease fears; …
Proactive and social navigation of autonomous vehicles in shared spaces
M Kabtoul - 2021 - theses.hal.science
The current trend in electric autonomous vehicles design is based on pre-existing models of
cities which have been built for cars. The carbon footprint of cities cannot be reduced until …
cities which have been built for cars. The carbon footprint of cities cannot be reduced until …