Motion planning is a fundamental research area in robotics. Sampling-based methods offer
an efficient solution for what is otherwise a rather challenging dilemma of path planning …

Motion planning is a vital module for unmanned aerial vehicles (UAVs), especially in
scenarios of autonomous navigation and operation. This survey delivers some recent state …

Quadrotors are agile. Unlike most other machines, they can traverse extremely complex
environments at high speeds. To date, only expert human pilots have been able to fully …

Autonomous vehicle (AV) software is typically composed of a pipeline of individual
components, linking sensor inputs to motor outputs. Erroneous component outputs …

We consider the problem of generating motion plans for a robot that are guaranteed to
succeed despite uncertainty in the environment, parametric model uncertainty, and …

This article deals with path planning of a mobile robot based on a grid map. Essential
assumption for path planning is a mobile robot with functional and reliable reactive …

Dynamically changing environments, unreliable state estimation, and operation under
severe resource constraints are fundamental challenges that limit the deployment of small …

During the last decade, sampling-based path planning algorithms, such as probabilistic
roadmaps (PRM) and rapidly exploring random trees (RRT), have been shown to work well …

Online solvers for partially observable Markov decision processes have been applied to
problems with large discrete state spaces, but continuous state, action, and observation …

Path planning is one of the most essential part in autonomous navigation. Most existing
works suppose that the environment is static and fixed. However, path planning is widely …