# Advanced Algorithms of Collision Free Navigation and Flocking for Autonomous UAVs

arXiv: https://arxiv.org/abs/2111.00166 · HTML: https://mlsanity.com/paper/2111.00166/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 28 of its 447 references that are in the map.
- First posted on arXiv 30 Oct 2021.

## Builds on (most cited first, 28 of 28)

- [ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras](https://mlsanity.com/paper/1610.06475/) (2016)
- [FUEL: Fast UAV Exploration using Incremental Frontier Structure and Hierarchical Planning](https://mlsanity.com/paper/2010.11561/) (2020)
- [MoreFusion: Multi-object Reasoning for 6D Pose Estimation from Volumetric Fusion](https://mlsanity.com/paper/2004.04336/) (2020)
- [Robust and Efficient Quadrotor Trajectory Generation for Fast Autonomous Flight](https://mlsanity.com/paper/1907.01531/) (2019)
- [An Efficient Sampling-based Method for Online Informative Path Planning in Unknown Environments](https://mlsanity.com/paper/1909.09548/) (2019)
- [MADER: Trajectory Planner in Multi-Agent and Dynamic Environments](https://mlsanity.com/paper/2010.11061/) (2020)
- [Nonlinear MPC for Collision Avoidance and Controlof UAVs With Dynamic Obstacles](https://mlsanity.com/paper/2008.00792/) (2020)
- [Efficient Optical flow and Stereo Vision for Velocity Estimation and Obstacle Avoidance on an Autonomous Pocket Drone](https://mlsanity.com/paper/1612.06702/) (2016)
- [FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments](https://mlsanity.com/paper/1903.03558/) (2019)
- [Voliro: An Omnidirectional Hexacopter With Tiltable Rotors](https://mlsanity.com/paper/1801.04581/) (2018)
- [Safe Local Exploration for Replanning in Cluttered Unknown Environments for Micro-Aerial Vehicles](https://mlsanity.com/paper/1710.00604/) (2017)
- [EVA-Planner: Environmental Adaptive Quadrotor Planning](https://mlsanity.com/paper/2011.04246/) (2020)
- [PANTHER: Perception-Aware Trajectory Planner in Dynamic Environments](https://mlsanity.com/paper/2103.06372/) (2021)
- [Robust Real-time UAV Replanning Using Guided Gradient-based Optimization and Topological Paths](https://mlsanity.com/paper/1912.12644/) (2019)
- [Perception-aware time optimal path parameterization for quadrotors](https://mlsanity.com/paper/2005.13986/) (2020)
- [Rectangular Pyramid Partitioning using Integrated Depth Sensors (RAPPIDS): A Fast Planner for Multicopter Navigation](https://mlsanity.com/paper/2003.01245/) (2020)
- [Design and optimal control of a tiltrotor micro aerial vehicle for efficient omnidirectional flight](https://mlsanity.com/paper/2003.09512/) (2020)
- [Mapless-Planner: A Robust and Fast Planning Framework for Aggressive Autonomous Flight without Map Fusion](https://mlsanity.com/paper/2011.03975/) (2020)
- [TGK-Planner: An Efficient Topology Guided Kinodynamic Planner for Autonomous Quadrotors](https://mlsanity.com/paper/2008.03468/) (2020)
- [Obstacle Avoidance through Deep Networks based Intermediate Perception](https://mlsanity.com/paper/1704.08759/) (2017)
- [Systematic design methodology for development and flight testing of a variable pitch quadrotor biplane VTOL UAV for payload delivery](https://mlsanity.com/paper/1801.02938/) (2018)
- [Proofs of Technical Results Justifying an Algorithm of Reactive 3D Navigation of a Mobile Robot through an Unknown Tunnel](https://mlsanity.com/paper/1803.00803/) (2018)
- [Real-Time Planning with Multi-Fidelity Models for Agile Flights in Unknown Environments](https://mlsanity.com/paper/1810.01035/) (2018)
- [An Open-Source System for Vision-Based Micro-Aerial Vehicle Mapping, Planning, and Flight in Cluttered Environments](https://mlsanity.com/paper/1812.03892/) (2018)
- [Joint Vision-Based Navigation, Control and Obstacle Avoidance for UAVs in Dynamic Environments](https://mlsanity.com/paper/1905.01187/) (2019)
- [OpEn: Code Generation for Embedded Nonconvex Optimization](https://mlsanity.com/paper/2003.00292/) (2020)
- [MAV Development Towards Navigation in Unknown and Dark Mining Tunnels](https://mlsanity.com/paper/2005.14433/) (2020)
- [Autonomous Flight through Cluttered Outdoor Environments Using a Memoryless Planner](https://mlsanity.com/paper/2103.12156/) (2021)

## Abstract (arXiv)

Unmanned aerial vehicles (UAVs) have become very popular for many military and civilian applications including in agriculture, construction, mining, environmental monitoring, etc. A desirable feature for UAVs is the ability to navigate and perform tasks autonomously with least human interaction. This is a very challenging problem due to several factors such as the high complexity of UAV applications, operation in harsh environments, limited payload and onboard computing power and highly nonlinear dynamics. The work presented in this report contributes towards the state-of-the-art in UAV control for safe autonomous navigation and motion coordination of multi-UAV systems. The first part of this report deals with single-UAV systems. The complex problem of three-dimensional (3D) collision-free navigation in unknown/dynamic environments is addressed. To that end, advanced 3D reactive control strategies are developed adopting the sense-and-avoid paradigm to produce quick reactions around obstacles. A special case of navigation in 3D unknown confined environments (i.e. tunnel-like) is also addressed. General 3D kinematic models are considered in the design which makes these methods applicable to different UAV types in addition to underwater vehicles. Moreover, different implementation methods for these strategies with quadrotor-type UAVs are also investigated considering UAV dynamics in the control design. Practical experiments and simulations were carried out to analyze the performance of the developed methods. The second part of this report addresses safe navigation for multi-UAV systems. Distributed motion coordination methods of multi-UAV systems for flocking and 3D area coverage are developed. These methods offer good computational cost for large-scale systems. Simulations were performed to verify the performance of these methods considering systems with different sizes.