相关论文: Towards Affective Drone Swarms: A Preliminary Crow…
Swarm dynamics is the study of collections of agents that interact with one another without central control. In natural systems, insects, birds, fish and other large mammals function in larger units to increase the overall fitness of the…
Over the past few decades, the research community has been interested in the study of multi-agent systems and their emerging collective dynamics. These systems are all around us in nature, like bacterial colonies, fish schools, bird flocks,…
A system of cooperative unmanned aerial vehicles (UAVs) is a group of agents interacting with each other and the surrounding environment to achieve a specific task. In contrast with a single UAV, UAV swarms are expected to benefit…
In order to be effective teammates, robots need to be able to understand high-level human behavior to recognize, anticipate, and adapt to human motion. We have designed a new approach to enable robots to perceive human group motion in…
Collective motion in animal groups, such as swarms of insects, flocks of birds, and schools of fish, are some of the most visually striking examples of emergent behavior. Empirical analysis of these behaviors in experiment or computational…
Recent advances in robotics bring us closer to the reality of living, co-habiting, and sharing personal spaces with robots. However, it is not clear how close a co-located robot can be to a human in a shared environment without making the…
We demonstrate the peer-to-peer impact of drones flying in close proximity. Understanding these impacts is crucial for planning efficient drone delivery services. In this regard, we conducted a set of experiments using drones at varying…
Nature is an inhabitant for enormous number of species. All the species do perform complex activities with simple and elegant rules for their survival. The property of emergence of collective behavior is remarkably supporting their…
We propose developing an integrated system to keep autonomous unmanned aircraft safely separated and behave as expected in conjunction with manned traffic. The main goal is to achieve safe manned-unmanned vehicle teaming to improve system…
Nowadays, companies such as Amazon, Alibaba, and even pizza chains are pushing forward to use drones, also called UAVs (Unmanned Aerial Vehicles), for service provision, such as package and food delivery. As governments intend to use these…
Unmanned aerial systems capable of beyond visual line of sight operation can be organized into a top-down hierarchy of layers including flight supervision, command and control, simulation of systems, operating systems, and physical…
Applications of large-scale mobile multi-robot systems can be beneficial over monolithic robots because of higher potential for robustness and scalability. Developing controllers for multi-robot systems is challenging because the multitude…
Previous research pays attention to how users strategically understand and consciously interact with algorithms but mainly focuses on an individual level, making it difficult to explore how users within communities could develop a…
Formal Modelling is often used as part of the design and testing process of software development to ensure that components operate within suitable bounds even in unexpected circumstances. In this paper, we use predictive formal modelling…
This article presents the world's first rapid drone flocking control using natural language through generative AI. The described approach enables the intuitive orchestration of a flock of any size to achieve the desired geometry. The key…
We demonstrate the possibility of learning drone swarm controllers that are zero-shot transferable to real quadrotors via large-scale multi-agent end-to-end reinforcement learning. We train policies parameterized by neural networks that are…
This paper aims to design quadrotor swarm performances, where the swarm acts as an integrated, coordinated unit embodying moving and deforming objects. We divide the task of creating a choreography into three basic steps: designing swarm…
The fast urbanization and climate change challenges require solutions that enable the efficient movement of people and goods in cities. We envision future cities to be composed of high-performing walkable districts where transportation…
Neurobiological theories of spatial cognition developed with respect to recording data from relatively small and/or simplistic environments compared to animals' natural habitats. It has been unclear how to extend theoretical models to large…
Individual agents in natural systems like flocks of birds or schools of fish display a remarkable ability to coordinate and communicate in local groups and execute a variety of tasks efficiently. Emulating such natural systems into drone…