[HTML][HTML] A survey of safety separation management and collision avoidance approaches of civil UAS operating in integration national airspace system
G **angmin, LYU Renli, SHI Hongxia, C Jun - Chinese Journal of …, 2020 - Elsevier
Recent years have witnessed a booming of the industry of civil Unmanned Aircraft System
(UAS). As an emerging industry, the UAS industry has been attracting great attention from …
(UAS). As an emerging industry, the UAS industry has been attracting great attention from …
Implicit personalization in driving assistance: State-of-the-art and open issues
In recent decades, driving assistance systems have been evolving towards personalization
for adapting to different drivers. With the consideration of driving preferences and driver …
for adapting to different drivers. With the consideration of driving preferences and driver …
FIRM: Sampling-based feedback motion-planning under motion uncertainty and imperfect measurements
AA Agha-Mohammadi… - … Journal of Robotics …, 2014 - journals.sagepub.com
In this paper we present feedback-based information roadmap (FIRM), a multi-query
approach for planning under uncertainty which is a belief-space variant of probabilistic …
approach for planning under uncertainty which is a belief-space variant of probabilistic …
Optimal stochastic vehicle path planning using covariance steering
This letter addresses the problem of vehicle path planning in the presence of obstacles and
uncertainties, a fundamental robotics problem. While several path planning algorithms have …
uncertainties, a fundamental robotics problem. While several path planning algorithms have …
Monte Carlo motion planning for robot trajectory optimization under uncertainty
This article presents a novel approach, named Monte Carlo Motion Planning (MCMP), to the
problem of motion planning under uncertainty, ie, to the problem of computing a low-cost …
problem of motion planning under uncertainty, ie, to the problem of computing a low-cost …
Stochastic dynamic games in belief space
Information gathering while interacting with other agents under sensing and motion
uncertainty is critical in domains such as driving, service robots, racing, or surveillance. The …
uncertainty is critical in domains such as driving, service robots, racing, or surveillance. The …
Chance-constrained sequential convex programming for robust trajectory optimization
Planning safe trajectories for nonlinear dynamical systems subject to model uncertainty and
disturbances is challenging. In this work, we present a novel approach to tackle chance …
disturbances is challenging. In this work, we present a novel approach to tackle chance …
High-frequency replanning under uncertainty using parallel sampling-based motion planning
As sampling-based motion planners become faster, they can be reexecuted more frequently
by a robot during task execution to react to uncertainty in robot motion, obstacle motion …
by a robot during task execution to react to uncertainty in robot motion, obstacle motion …
Stochastic extended LQR: Optimization-based motion planning under uncertainty
We introduce a novel optimization-based motion planner, Stochastic Extended LQR
(SELQR), which computes a trajectory and associated linear control policy with the objective …
(SELQR), which computes a trajectory and associated linear control policy with the objective …
Colag: A collaborative air-ground framework for perception-limited ugvs' navigation
Perception is necessary for autonomous navigation in an unknown area crowded with
obstacles. It's challenging for a robot to navigate safely without any sensors that can sense …
obstacles. It's challenging for a robot to navigate safely without any sensors that can sense …