As the rapid development of robotics, Micro Aerial Vehicles (MAV) have been more and more popular in our daily life. One of the key modules to perform autonomous navigation is motion planning.

In this thesis, we firstly demonstrate a perception-planning-control pipeline to give the overview pipeline. Then we focus on motion planning methods, which can be roughly divided into two parts, hard-constrained methods and soft-constrained methods.

For hard-constrained motion planning methods, we follow previous work in our lab generally, to construct piecewise Bezier curves in convex flying corridors to describe the trajectory. However, in this thesis, convex polyhedrons generated by IRIS method instead of simple cuboids are used to form convex flying corridors. This way avoids the...[ Read more ]

As the rapid development of robotics, Micro Aerial Vehicles (MAV) have been more and more popular in our daily life. One of the key modules to perform autonomous navigation is motion planning.

In this thesis, we firstly demonstrate a perception-planning-control pipeline to give the overview pipeline. Then we focus on motion planning methods, which can be roughly divided into two parts, hard-constrained methods and soft-constrained methods.

For hard-constrained motion planning methods, we follow previous work in our lab generally, to construct piecewise Bezier curves in convex flying corridors to describe the trajectory. However, in this thesis, convex polyhedrons generated by IRIS method instead of simple cuboids are used to form convex flying corridors. This way avoids the loss of free space, and a more elegant trajectory can be generated.

For soft-constrained motion planning methods, Euclidean Signed Distance Field (ESDF) is a useful and neccessary tool, since it can easily query the distance and gradient information against obstacles. Fast incrementally built ESDF map is the bottleneck for conducting real-time motion planning. In this paper, we investigate this problem and propose a mapping system called FIESTA to build global ESDF map incrementally. By introducing two independent updating queues for inserting and deleting obstacles separately, and using Indexing Data Structures and Doubly Linked Lists for map maintenance, our algorithm updates as few as possible nodes using a BFS framework. Our ESDF map has high computational performance and produces near-optimal results. We show our method outperforms other up-to-date methods in term of performance and accuracy by both theory and experiments. We integrate FIESTA into a completed quadrotor system and validate it by both simulation and onboard experiments. We release our method as open-source software for the community¹.

____________________________

¹https://github.com/hlx1996/FIESTA