相关论文: Dolphin: a task orchestration language for autonom…
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…
Robots navigating in human environments should use language to ask for assistance and be able to understand human responses. To study this challenge, we introduce Cooperative Vision-and-Dialog Navigation, a dataset of over 2k embodied,…
The growing demand for real-time, safety-critical systems has significantly increased both the adoption and complexity of Time Sensitive Networking (TSN). Configuring an optimized TSN network is highly challenging, requiring careful…
Vision-and-Language Navigation (VLN) presents a complex challenge in embodied AI, requiring agents to interpret natural language instructions and navigate through visually rich, unfamiliar environments. Recent advances in large…
The integration of foundation models (FMs) into robotics has enabled robots to understand natural language and reason about the semantics in their environments. However, existing FM-enabled robots primary operate in closed-world settings,…
The Fifth International Workshop on Domain-Specific Languages and Models for Robotic Systems (DSLRob'14) was held in conjunction with the 2014 International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR…
Artificial intelligence (AI) assisted unmanned aerial vehicle (UAV) aided next-generation networking is proposed for dynamic environments. In the AI-enabled UAV-aided wireless networks (UAWN), multiple UAVs are employed as aerial base…
Dragonfly is a deep reinforcement learning library focused on modularity, in order to ease experimentation and developments. It relies on a json serialization that allows to swap building blocks and perform parameter sweep, while minimizing…
The inherent probabilistic nature of Large Language Models (LLMs) introduces an element of unpredictability, raising concerns about potential discrepancies in their output. This paper introduces an innovative approach aims to generate…
With the increasing demand for dynamic behaviors in automotive use cases, Software Defined Vehicles (SDVs) have emerged as a promising solution by bringing dynamic onboard service management capabilities. While users may request a wide…
Unmanned aerial vehicular network (UAVN) is envisioned to provide flexible connectivity, wide-area coverage, and low-latency services in dynamic environments. From an agentic artificial intelligence (Agentic AI) perspective, UAVNs naturally…
In this demo paper, we introduce the DARPA D3M program for automatic machine learning (ML) and JPL's MARVIN tool that provides an environment to locate, annotate, and execute machine learning primitives for use in ML pipelines. MARVIN is a…
Underwater multi-robot cooperative coverage remains challenging due to partial observability, limited communication, environmental uncertainty, and the lack of access to global localization. To address these issues, this paper presents a…
In the real world, unmanned surface vehicles (USV) often need to coordinate with each other to accomplish specific tasks. However, achieving cooperative control in multi-agent systems is challenging due to issues such as non-stationarity…
This paper presents an approach for defining Unmanned Aerial Vehicle (UAV) missions on a high level. Current methods for UAV mission specification are evaluated and their deficiencies are analyzed. From these findings, a new graphical…
Adapting trajectories to dynamic situations and user preferences is crucial for robot operation in unstructured environments with non-expert users. Natural language enables users to express these adjustments in an interactive manner. We…
Autonomous navigation for Unmanned Aerial Vehicles faces key challenges from limited onboard computational resources, which restrict deployed deep neural networks to shallow architectures incapable of handling complex environments.…
In this paper, task offloading from vehicles with random velocities is optimized via a novel dynamic programming framework. Particularly, in a vehicular network with multiple vehicles and base stations (BSs), computing tasks of vehicles are…
The next generation networks offers significant potential to advance Intelligent Transportation Systems (ITS), particularly through the integration of Digital Twins (DTs). However, ensuring the uninterrupted operation of DTs through…
Teleoperation is a key enabler for future mobility, supporting Automated Vehicles in rare and complex scenarios beyond the capabilities of their automation. Despite ongoing research, no open source software currently combines Remote…