相关论文: Industry Led Use-Case Development for Human-Swarm …
Despite significant research, robotic swarms have yet to be useful in solving real-world problems, largely due to the difficulty of creating and controlling swarming behaviors in multi-agent systems. Traditional top-down approaches in which…
A human-swarm cooperative system, which mixes multiple robots and a human supervisor to form a heterogeneous team, is widely used for emergent scenarios such as criminal tracking in social security and victim assistance in a natural…
In this work, we explore emergent behaviors by swarms of anonymous, homogeneous, non-communicating, reactive robots that do not know their global position and have limited relative sensing. We introduce a novel method that enables such…
With recent advances in artificial intelligence (AI) and robotics, unmanned vehicle swarms have received great attention from both academia and industry due to their potential to provide services that are difficult and dangerous to perform…
Engineering swarms of cyber-physical systems (CPSs) is a complex process. We present the CPSwarm workbench that creates an automated design workflow to ease this process. This formalized workflow guides the user from modeling, to code…
In this paper, we extended previous studies of cooperating autonomous robots to include situations when environmental changes and changes in the number of robots in the swarm can affect the efficiency to execute tasks assigned to the swarm…
The development and deployment of automated vehicles pose major challenges for manufacturers to this day. Whilst central questions, like the issue of ensuring a sufficient level of safety, remain unanswered, prototypes are increasingly…
Swarm protocols are a recently introduced formalism for specifying, implementing, and verifying peer-to-peer systems called swarms. A swarm consists of distributed agents called machines that communicate by asynchronous event propagation.…
Despite the advantages of having robot swarms, human supervision is required for real-world applications. The performance of the human-swarm system depends on several factors including the data availability for the human operators. In this…
With recent advancements in AI and computation tools, intelligent paradigms emerged to empower different fields such as healthcare robots with new capabilities. Advanced AI robotic algorithms (e.g., reinforcement learning) can be trained…
Despite the advances made in artificial intelligence, software agents, and robotics, there is little we see today that we can truly call a fully autonomous system. We conjecture that the main inhibitor for advancing autonomy is lack of…
As intelligent agents transition from controlled to uncontrolled environments, they face challenges that sometimes exceed their operational capabilities. In many scenarios, they rely on assistance from bystanders to overcome those…
The integration of agentic AI, powered by large language models (LLMs) with autonomous reasoning, planning, and execution, into unmanned aerial vehicle (UAV) swarms opens new operational possibilities and brings the vision of the Internet…
Multi-robot systems are an efficient method to explore and map an unknown environment. The simulataneous localization and mapping (SLAM) algorithm is common for single robot systems, however multiple robots can share respective map data in…
A new and relatively unexplored research direction in robotics systems is the coordination of humans and robots working as a team. In this paper, we focus upon problem domains and tasks in which multiple robots, humans and other agents are…
Artificial swarm systems have been extensively studied and used in computer science, robotics, engineering and other technological fields, primarily as a platform for implementing robust distributed systems to achieve pre-defined…
Technological evolution in the field of robotics is emerging with major breakthroughs in recent years. This was especially fostered by revolutionary new software applications leading to humanoid robots. Humanoids are being envisioned for…
For autonomous vehicles, safe navigation in complex environments depends on handling a broad range of diverse and rare driving scenarios. Simulation- and scenario-based testing have emerged as key approaches to development and validation of…
Achieving greater autonomy in automation systems is crucial for handling unforeseen situations effectively. However, this remains challenging due to technological limitations and the complexity of real-world environments. This paper…
More widespread adoption requires swarms of robots to be more flexible for real-world applications. Multiple challenges remain in complex scenarios where a large amount of data needs to be processed in real-time and high degrees of…