Path planning constitutes one of the most crucial abilities an autonomous robot should
possess, apart from Simultaneous Localization and Mapping algorithms (SLAM) and …

Robust planning under uncertainty is critical for robots in uncertain, dynamic environments,
but incurs high computational cost. State-of-the-art online search algorithms, such as …

Parallel search algorithms harness the multithreading capability of modern processors to
achieve faster planning. One such algorithm is PA* SE (Parallel A* for Slow Expansions) …

For robots using motion planning algorithms such as RRT and RRT*, the computational load
can vary by orders of magnitude as the complexity of the local environment changes. To …

The autonomous navigation of vehicles typically combines two kinds of methods: a path is
first planned, and then the robot is driven by a local obstacle-avoidance controller. The …

Lazy search algorithms have been developed to efficiently solve planning problems in
domains where the computational effort is dominated by the cost of edge evaluation. The …

We present Parallel Rapidly Exploring Random Tree (PRRT) and Parallel RRT*(PRRT*),
which are sampling-based methods for feasible and optimal motion planning designed for …

Trajectory optimization is a widely used technique in robot motion planning for letting the
dynamics and constraints on the system shape and synthesize complex behaviors. Several …

Path planning is of crucial importance for au-tonomous mobile robots, and comes with a
wide range of real-world applications including transportation, surveillance, and rescue …

Autonomous microrobots have been utilized in a wide range of applications. Energy-
efficient, real-time path planning for navigation is essential. This work presents a path …