Tootfinder

The Search for Relevance: A Context-Aware Paradigm Shift in Semantic and Task-Oriented V2X Communications
Luca Lusvarghi, Javier Gozalvez, Baldomero Coll-Perales, Mohammad Irfan Khan, Miguel Sepulcre, Seyhan Ucar, Onur Altintas
https://arxiv.org/abs/2508.07394

The Search for Relevance: A Context-Aware Paradigm Shift in Semantic and Task-Oriented V2X Communications
The design of communication systems has traditionally focused on the reliable and timely delivery of data. However, the scalability challenges faced by the evolution to a 6G-driven society demand new communication paradigms that carefully curate the content being transmitted. This paper envisions a joint semantic and task-oriented communication paradigm where Connected and Autonomous Vehicles (CAVs) transmit only the information necessary to convey the desired meaning that is relevant to the in…

Toward Goal-Oriented Communication in Multi-Agent Systems: An overview
Themistoklis Charalambous, Nikolaos Pappas, Nikolaos Nomikos, Risto Wichman
https://arxiv.org/abs/2508.07720

Toward Goal-Oriented Communication in Multi-Agent Systems: An overview
As multi-agent systems (MAS) become increasingly prevalent in autonomous systems, distributed control, and edge intelligence, efficient communication under resource constraints has emerged as a critical challenge. Traditional communication paradigms often emphasize message fidelity or bandwidth optimization, overlooking the task relevance of the exchanged information. In contrast, goal-oriented communication prioritizes the importance of information with respect to the agents' shared objectives…

Understanding Pedestrian Gesture Misrecognition: Insights from Vision-Language Model Reasoning
Tram Thi Minh Tran, Xinyan Yu, Callum Parker, Julie Stephany Berrio Perez, Stewart Worrall, Martin Tomitsch
https://arxiv.org/abs/2508.06801

Understanding Pedestrian Gesture Misrecognition: Insights from Vision-Language Model Reasoning
Pedestrian gestures play an important role in traffic communication, particularly in interactions with autonomous vehicles (AVs), yet their subtle, ambiguous, and context-dependent nature poses persistent challenges for machine interpretation. This study investigates these challenges by using GPT-4V, a vision-language model, not as a performance benchmark but as a diagnostic tool to reveal patterns and causes of gesture misrecognition. We analysed a public dataset of pedestrian-vehicle interact…

A Hybrid TDMA/CSMA Protocol for Time-Sensitive Traffic in Robot Applications
Shiqi Xu, Lihao Zhang, Yuyang Du, Qun Yang, Soung Chang Liew
https://arxiv.org/abs/2509.06119 https:…

A Hybrid TDMA/CSMA Protocol for Time-Sensitive Traffic in Robot Applications
Recent progress in robotics has underscored the demand for real-time control in applications such as manufacturing, healthcare, and autonomous systems, where the timely delivery of mission-critical commands under heterogeneous robotic traffic is paramount for operational efficacy and safety. In these scenarios, mission-critical traffic follows a strict deadline-constrained communication pattern: commands must arrive within defined QoS deadlines, otherwise late arrivals can degrade performance o…

Social-Pose: Enhancing Trajectory Prediction with Human Body Pose
Yang Gao, Saeed Saadatnejad, Alexandre Alahi
https://arxiv.org/abs/2507.22742 https://arx…

Social-Pose: Enhancing Trajectory Prediction with Human Body Pose
Accurate human trajectory prediction is one of the most crucial tasks for autonomous driving, ensuring its safety. Yet, existing models often fail to fully leverage the visual cues that humans subconsciously communicate when navigating the space. In this work, we study the benefits of predicting human trajectories using human body poses instead of solely their Cartesian space locations in time. We propose `Social-pose', an attention-based pose encoder that effectively captures the poses of all …

Network-Aware Control of AGVs in an Industrial Scenario: A Simulation Study Based on ROS 2 and Gazebo
Filippo Bragato, Tullia Fontana, Marco Giordani, Malte Schellmann, Josef Eichinger, Michele Zorzi
https://arxiv.org/abs/2509.06451

Network-Aware Control of AGVs in an Industrial Scenario: A Simulation Study Based on ROS 2 and Gazebo
Networked Control System (NCS) is a paradigm where sensors, controllers, and actuators communicate over a shared network. One promising application of NCS is the control of Automated Guided Vehicles (AGVs) in the industrial environment, for example to transport goods efficiently and to autonomously follow predefined paths or routes. In this context, communication and control are tightly correlated, a paradigm referred to as Joint Communication and Control (JCC), since network issues such as del…

Stability-Aware Joint Communication and Control for Nonlinear Control-Non-Affine Wireless Networked Control Systems
Rasika Vijithasena, Rafaela Scaciota, Mehdi Bennis, Sumudu Samarakoon
https://arxiv.org/abs/2509.02247

Stability-Aware Joint Communication and Control for Nonlinear Control-Non-Affine Wireless Networked Control Systems
Ensuring the stability of wireless networked control systems (WNCS) with nonlinear and control-non-affine dynamics, where system behavior is nonlinear with respect to both states and control decisions, poses a significant challenge, particularly under limited resources. However, it is essential in the context of 6G, which is expected to support reliable communication to enable real-time autonomous systems. This paper proposes a joint communication and control solution consisting of: i) a deep K…

Latency Minimization for Multi-AAV-Enabled ISCC Systems with Movable Antenna
Yiyang Chen, Wenchao Liu, Chunjie Wang, Yinyu Wu, Xuhui Zhang, Yanyan Shen
https://arxiv.org/abs/2508.05574

Latency Minimization for Multi-AAV-Enabled ISCC Systems with Movable Antenna
This paper investigates an autonomous aerial vehicle (AAV)-enabled integrated sensing, communication, and computation system, with a particular focus on integrating movable antennas (MAs) into the system for enhancing overall system performance. Specifically, multiple MA-enabled AVVs perform sensing tasks and simultaneously transmit the generated computational tasks to the base station for processing. To minimize the maximum latency under the sensing and resource constraints, we formulate an op…

ACCESS-AV: Adaptive Communication-Computation Codesign for Sustainable Autonomous Vehicle Localization in Smart Factories
Rajat Bhattacharjya, Arnab Sarkar, Ish Kool, Sabur Baidya, Nikil Dutt
https://arxiv.org/abs/2507.20399

ACCESS-AV: Adaptive Communication-Computation Codesign for Sustainable Autonomous Vehicle Localization in Smart Factories
Autonomous Delivery Vehicles (ADVs) are increasingly used for transporting goods in 5G network-enabled smart factories, with the compute-intensive localization module presenting a significant opportunity for optimization. We propose ACCESS-AV, an energy-efficient Vehicle-to-Infrastructure (V2I) localization framework that leverages existing 5G infrastructure in smart factory environments. By opportunistically accessing the periodically broadcast 5G Synchronization Signal Blocks (SSBs) for local…

AoI-Aware Resource Allocation with Deep Reinforcement Learning for HAPS-V2X Networks
Ahmet Melih Ince, Ayse Elif Canbilen, Halim Yanikomeroglu
https://arxiv.org/abs/2508.00011 h…

AoI-Aware Resource Allocation with Deep Reinforcement Learning for HAPS-V2X Networks
Sixth-generation (6G) networks are designed to meet the hyper-reliable and low-latency communication (HRLLC) requirements of safety-critical applications such as autonomous driving. Integrating non-terrestrial networks (NTN) into the 6G infrastructure brings redundancy to the network, ensuring continuity of communications even under extreme conditions. In particular, high-altitude platform stations (HAPS) stand out for their wide coverage and low latency advantages, supporting communication rel…