Unmanned aerial vehicles (uavs): Collision avoidance systems and approaches
Moving towards autonomy, unmanned vehicles rely heavily on state-of-the-art collision
avoidance systems (CAS). A lot of work is being done to make the CAS as safe and reliable …
avoidance systems (CAS). A lot of work is being done to make the CAS as safe and reliable …
Image based techniques for crack detection, classification and quantification in asphalt pavement: a review
Pavement condition information is a significant component in Pavement Management
Systems. The labeling and quantification of the type, severity, and extent of surface cracking …
Systems. The labeling and quantification of the type, severity, and extent of surface cracking …
Swarm intelligence and cyber-physical systems: concepts, challenges and future trends
Swarm Intelligence (SI) is a popular multi-agent framework that has been originally inspired
by swarm behaviors observed in natural systems, such as ant and bee colonies. In a system …
by swarm behaviors observed in natural systems, such as ant and bee colonies. In a system …
A survey on swarm microrobotics
The small size and wireless actuation of microrobots make them potential candidates for
minimally invasive medicine. To advance microrobots to future clinical application …
minimally invasive medicine. To advance microrobots to future clinical application …
[HTML][HTML] Improving multi-target cooperative tracking guidance for UAV swarms using multi-agent reinforcement learning
Z Wenhong, LI Jie, LIU Zhihong, S Lincheng - Chinese Journal of …, 2022 - Elsevier
Abstract Multi-Target Tracking Guidance (MTTG) in unknown environments has great
potential values in applications for Unmanned Aerial Vehicle (UAV) swarms. Although Multi …
potential values in applications for Unmanned Aerial Vehicle (UAV) swarms. Although Multi …
Multi-target tracking for unmanned aerial vehicle swarms using deep reinforcement learning
W Zhou, Z Liu, J Li, X Xu, L Shen - Neurocomputing, 2021 - Elsevier
In recent years, deep reinforcement learning (DRL) has proved its great potential in multi-
agent cooperation. However, how to apply DRL to multi-target tracking (MTT) problem for …
agent cooperation. However, how to apply DRL to multi-target tracking (MTT) problem for …
Balancing collective exploration and exploitation in multi-agent and multi-robot systems: A review
Multi-agent systems and multi-robot systems have been recognized as unique solutions to
complex dynamic tasks distributed in space. Their effectiveness in accomplishing these …
complex dynamic tasks distributed in space. Their effectiveness in accomplishing these …
Past, present, and future of swarm robotics
AR Cheraghi, S Shahzad, K Graffi - Intelligent Systems and Applications …, 2022 - Springer
Swarm Robotics is an emerging field of adapting the phenomenon of natural swarms to
robotics and a study of robots to mimic natural swarms, like ants and birds, to form a …
robotics and a study of robots to mimic natural swarms, like ants and birds, to form a …
Market approaches to the multi-robot task allocation problem: a survey
Market-based methods have received significant attention for solving the multi-robot task
allocation problem. They have been used in a variety of multi-robot scenarios, such as …
allocation problem. They have been used in a variety of multi-robot scenarios, such as …
Swarm robotics: Simulators, platforms and applications review
This paper presents an updated and broad review of swarm robotics research papers
regarding software, hardware, simulators and applications. The evolution from its concept to …
regarding software, hardware, simulators and applications. The evolution from its concept to …