DSSE: a drone swarm search environment
The Drone Swarm Search project is an environment, based on PettingZoo, that is to be used in conjunction with multi-agent (or single-agent) reinforcement learning algorithms. It is an environment in which the agents (drones), have to find the targets (shipwrecked people). The agents do not know the position of the target and do not receive rewards related to their own distance to the target(s). However, the agents receive the probabilities of the target(s) being in a certain cell of the map. The aim of this project is to aid in the study of reinforcement learning algorithms that require dynamic probabilities as inputs.
Code (1)
Tasks
Positionreinforcement-learningReinforcement LearningSimilar Papers 제목 키워드 기반
Drone swarm patrolling with uneven coverage requirements
Swarms of drones are being more and more used in many practical scenarios, such as surveillance, environmental monitoring, search and rescue in hardly-accessible areas, etc.. While a single drone can be guided by a human…
Deep Reinforcement LearningTowards Brain-Computer Interfaces for Drone Swarm Control
Noninvasive brain-computer interface (BCI) decodes brain signals to understand user intention. Recent advances have been developed for the BCI-based drone control system as the demand for drone control increases. Especia…
Brain Computer InterfaceEEGElectroencephalogram (EEG)General ClassificationAttentionSwarm: Reinforcement Learning with Attention Control Barier Function for Crazyflie Drones in Dynamic Environments
We introduce AttentionSwarm, a novel benchmark designed to evaluate safe and efficient swarm control across three challenging environments: a landing environment with obstacles, a competitive drone game setting, and a dy…
Collision AvoidanceAdvanced Drone Swarm Security by Using Blockchain Governance Game
This research contributes to the security design of an advanced smart drone swarm network based on a variant of the Blockchain Governance Game (BGG), which is the theoretical game model to predict the moments of security…
An Autonomous Drone Swarm for Detecting and Tracking Anomalies among Dense Vegetation
Swarms of drones offer an increased sensing aperture, and having them mimic behaviors of natural swarms enhances sampling by adapting the aperture to local conditions. We demonstrate that such an approach makes detecting…
Anomaly Detection