# DCAD: Decentralized Collision Avoidance with Dynamics Constraints for Agile Quadrotor Swarms

arXiv: https://arxiv.org/abs/1909.03961 · HTML: https://mlsanity.com/paper/1909.03961/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Sep 2019.

## Built on by (most cited first, 1 of 1)

- [Collision Avoidance for Multiple UAVs in Unknown Scenarios with Causal Representation Disentanglement](https://mlsanity.com/paper/2407.04064/) (2024)

## Abstract (arXiv)

We present a novel, decentralized collision avoidance algorithm for navigating a swarm of quadrotors in dense environments populated with static and dynamic obstacles. Our algorithm relies on the concept of Optimal Reciprocal CollisionAvoidance (ORCA) and utilizes a flatness-based Model Predictive Control (MPC) to generate local collision-free trajectories for each quadrotor. We feedforward linearize the non-linear dynamics of the quadrotor and subsequently use this linearized model in our MPC framework. Our method is downwash conscious and computes safe trajectories that avoid quadrotors from entering each other's downwash regions during close proximity maneuvers. In addition, we account for the uncertainty in sensed position and velocity data using Kalman filtering. We evaluate the performance of our algorithm with other state-of-the-art methods and demonstrate its superior performance in terms of smoothness of generated trajectories and lower probability of collision during high velocity maneuvers.