On the Effects of Collision Avoidance on Emergent Swarm Behavior

by   Chris Taylor, et al.

Swarms of autonomous agents, through their decentralized and robust nature, show great promise as a future solution to the myriad missions of business, military, and humanitarian relief. The diverse nature of mission sets creates the need for swarm algorithms to be deployed on a variety of hardware platforms. Swarms are currently viable on platforms where collisions between agents are harmless, but on many platforms collisions are prohibited since they would damage the agents involved. The available literature typically assumes that collisions can be avoided by adding a collision avoidance algorithm on top of an existing swarm behavior. Through an illustrative example in our experience replicating a particular behavior, we show that this can be difficult to achieve since the swarm behavior can be disrupted by the collision avoidance. We introduce metrics quantifying the level of disruption in our swarm behavior and propose a technique that is able to assist in tuning the collision avoidance algorithm such that the goal behavior is achieved as best as possible while collisions are avoided. We validate our results through simulation.


Decentralized Swarm Collision Avoidance for Quadrotors via End-to-End Reinforcement Learning

Collision avoidance algorithms are of central interest to many drone app...

Distributed Swarm Collision Avoidance Based on Angular Calculations

Collision avoidance is one of the most important topics in the robotics ...

Stigmergy-based collision-avoidance algorithm for self-organising swarms

Real-time multi-agent collision-avoidance algorithms comprise a key enab...

LSwarm: Efficient Collision Avoidance for Large Swarms with Coverage Constraints in Complex Urban Scenes

In this paper, we address the problem of collision avoidance for a swarm...

Learning-'N-Flying: A Learning-based, Decentralized Mission Aware UAS Collision Avoidance Scheme

Urban Air Mobility, the scenario where hundreds of manned and Unmanned A...

Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning

Robots that navigate among pedestrians use collision avoidance algorithm...

Please sign up or login with your details

Forgot password? Click here to reset