Decentralized 3D Collision Avoidance for Multiple UAVs in Outdoor Environments

Abstract

The use of multiple aerial vehicles for autonomous missions is turning into commonplace. In many of these applications, the Unmanned Aerial Vehicles (UAVs) have to cooperate and navigate in a shared airspace, becoming 3D collision avoidance a relevant issue. Outdoor scenarios impose additional challenges: (i) accurate positioning systems are costly; (ii) communication can be unreliable or delayed; and (iii) external conditions like wind gusts affect UAVs’ maneuverability. In this paper, we present 3D-SWAP, a decentralized algorithm for 3D collision avoidance with multiple UAVs. 3D-SWAP operates reactively without high computational requirements and allows UAVs to integrate measurements from their local sensors with positions of other teammates within communication range. We tested 3D-SWAP with our team of custom-designed UAVs. First, we used a Software-In-The-Loop simulator for system integration and evaluation. Second, we run field experiments with up to three UAVs in an outdoor scenario with uncontrolled conditions (i.e., noisy positioning systems, wind gusts, etc). We report our results and our procedures for this field experimentation.

DCAD: Decentralized Collision Avoidance With Dynamics Constraints for Agile Quadrotor Swarms

“…In prior literature, the downwash effect is considered in collision avoidance by modeling the agents as axis-aligned ellipsoids [7], [5] or cylinders [30], [12], which encourages a larger separation along the Zaxis. Quadrotor roll and pitch affect the downwash region, and the ellipsoid or cylinder must be rotated with respect to the quadrotor orientation for accurate modeling [12]. For simplicity, the quadrotors are modeled as axis-aligned ellipsoids and the radius of the ellipsoid/cylinder is increased by a safety threshold to account for roll and pitch [12] [30].…”

“…Quadrotor roll and pitch affect the downwash region, and the ellipsoid or cylinder must be rotated with respect to the quadrotor orientation for accurate modeling [12]. For simplicity, the quadrotors are modeled as axis-aligned ellipsoids and the radius of the ellipsoid/cylinder is increased by a safety threshold to account for roll and pitch [12] [30].…”

EAOA: Energy-Aware Grid-Based 3D-Obstacle Avoidance in Coverage Path Planning for UAVs

“…Different research works [13,15,16] rely on either two-dimensional or three-dimensional methods for obstacle detection and avoidance. In [17], a 3D-SWAP technique for 3D collision avoidance with multiple UAVs is proposed. UAVs rely on local data from sensors and positions of other neighboring UAVs.…”

“…Recent approaches in 3D path planning concentrate more on detecting and avoiding obstacle in a 3D view [13][14][15][16][17][18][19]. They have not given priority to compromise between the energy efficiency and the completeness of the area coverage [20] in the presence of obstacles.…”

Autonomous Execution of Cinematographic Shots With Multiple Drones

“…Additionally, the Shot Executor needs to take care of collision avoidance for safety reasons. For that, we used a reactive algorithm for collision avoidance in multi-drone teams [42]. In previous work, we developed that algorithm to resolve drone conflicts (i.e., possible collisions) with other teammates or external obstacles in a decentralized manner, applying roundabout maneuvers to avoid each other.…”