6G Empowering Future Robotics: A Vision for Next-Generation Autonomous Systems

• URL: http://arxiv.org/abs/2602.12246v1
• Date: Thu, 12 Feb 2026 18:31:24 GMT
• Title: 6G Empowering Future Robotics: A Vision for Next-Generation Autonomous Systems
• Abstract summary: This paper examines the transformative impact of 6G on enhancing key robotics functionalities.<n>It provides a systematic mapping of IMT-2030 key performance indicators to robotic functional blocks including sensing, perception, cognition, actuation and self-learning.<n>Building upon this mapping, we propose a high-level architectural framework integrating robotic, intelligent, and network service planes.
• Score: 4.645526475390433
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The convergence of robotics and next-generation communication is a critical driver of technological advancement. As the world transitions from 5G to 6G, the foundational capabilities of wireless networks are evolving to support increasingly complex and autonomous robotic systems. This paper examines the transformative impact of 6G on enhancing key robotics functionalities. It provides a systematic mapping of IMT-2030 key performance indicators to robotic functional blocks including sensing, perception, cognition, actuation and self-learning. Building upon this mapping, we propose a high-level architectural framework integrating robotic, intelligent, and network service planes, underscoring the need for a holistic approach. As an example use case, we present a real-time, dynamic safety framework enabled by IMT-2030 capabilities for safe and efficient human-robot collaboration in shared spaces.

Related papers

• Learning Physical Interaction: A Survey of Tactile- and Force-aware Robot Learning [128.76135832773102]
  Physically grounded robot intelligence requires robots to perceive, reason about, and regulate their interactions with the physical world.<n>Recent robot learning methods have made substantial progress by integrating force, tactile, vision, language, and proprioceptive sensing into learned manipulation policies.<n>Despite these advances, existing surveys have not explicitly reviewed force- and tactile-aware robot learning from a unified perspective.
  arXiv  Detail & Related papers  (2026-08-02T14:22:01Z)
• AI-IoT-Robotics Integration: Survey of Frameworks, Emerging Trends, and the Path Toward Connected Robotics [1.4337588659482519]
  The convergence of Artificial Intelligence, the Internet of Things, and Robotics is no longer a futuristic vision.<n>Despite progress in pairwise combinations such as AIoT and the Internet of Robotic Things (IoRT), there remains a lack of unified design frameworks that fully integrate all three.<n>This survey synthesizes the state-of-the-art across these domains, emphasizing the emerging role of Small Language Models (SLMs) at the edge and Large Language Models (LLMs) in the cloud.
  arXiv  Detail & Related papers  (2026-05-31T05:10:34Z)
• Empowering Embodied AI in 6G Networks: Architecture, Enablers, and Open Challenges [29.55746814021036]
  Embodied artificial intelligence (AI) is emerging as a key driver of the sixth-generation (6G) wireless networks.<n>We present a holistic framework for embodied AI-native 6G systems, in which communication, sensing, computation, and control are jointly designed as a unified closed-loop infrastructure.
  arXiv  Detail & Related papers  (2026-05-17T09:34:57Z)
• End-to-End O-RAN Testbed for Edge-AI-Enabled 5G/6G Connected Industrial Robotics [1.2179379138011863]
  We present a 5G/6G O-RAN-based end-to-end testbed that integrates E-AI for connected industrial robotic applications.<n>The testbed is used to investigate trade-offs among different data acquisition, edge processing, and real-time streaming approaches for robotic perception.
  arXiv  Detail & Related papers  (2026-03-13T20:14:32Z)
• Robotic Grasping and Placement Controlled by EEG-Based Hybrid Visual and Motor Imagery [64.82869118243723]
  We present a framework that integrates EEG-based visual and motor imagery (VI/MI) with robotic control to enable real-time, intention-driven grasping and placement.<n>Motivated by the promise of BCI-driven robotics, this system bridges neural signals with physical control by deploying offline-pretrained decoders in a zero-shot manner.
  arXiv  Detail & Related papers  (2026-03-03T17:41:42Z)
• Heterogeneous computing platform for real-time robotics [1.9219370642303344]
  New concept of Society 5.0 is emerging, in which infrastructure of a city will be instrumented to increase reliability, efficiency, and safety.<n>We show how we can combine neuromorphic computing hardware, for sensing and real-time perception and interaction with a local AI compute cluster.<n>We demonstrate the use of this hybrid computing architecture in an interactive task, in which a humanoid robot plays a musical instrument with a human.
  arXiv  Detail & Related papers  (2026-01-13T11:48:25Z)
• RobotSeg: A Model and Dataset for Segmenting Robots in Image and Video [56.9581053843815]
  We introduce RobotSeg, a foundation model for robot segmentation in image and video.<n>It addresses the lack of adaptation to articulated robots, reliance on manual prompts, and the need for per-frame training mask annotations.<n>It achieves state-of-the-art performance on both images and videos.
  arXiv  Detail & Related papers  (2025-11-28T07:51:02Z)
• Procedimiento de auditoría de ciberseguridad para sistemas autónomos: metodología, amenazas y mitigaciones [0.1759008116536278]
  This article presents a specific security auditing procedure for autonomous systems.<n>It is based on a layer-structured methodology, a threat taxonomy adapted to the robotic context, and concrete mitigation measures.
  arXiv  Detail & Related papers  (2025-11-07T12:06:21Z)
• Embodied AI with Foundation Models for Mobile Service Robots: A Systematic Review [4.540236408836132]
  We present the first systematic review of the integration of foundation models in mobile service robotics.<n>We explore the role of such models in enabling real-time sensor fusion, language-conditioned control, and adaptive task execution.<n>We also discuss real-world applications in the domestic assistance, healthcare, and service automation sectors.
  arXiv  Detail & Related papers  (2025-05-26T20:08:09Z)
• Redefining Robot Generalization Through Interactive Intelligence [0.0]
  We argue that robot foundation models must evolve to an interactive multi-agent perspective in order to handle the complexities of real-time human-robot co-adaptation.<n>By moving beyond single-agent designs, our position emphasizes how foundation models in robotics can achieve a more robust, personalized, and anticipatory level of performance.
  arXiv  Detail & Related papers  (2025-02-09T17:13:27Z)
• Overview of AI and Communication for 6G Network: Fundamentals, Challenges, and Future Research Opportunities [148.601430677814]
  This paper presents a comprehensive overview of AI and communication for 6G networks.<n>We first review the driving factors behind incorporating AI into wireless communications, as well as the vision for the convergence of AI and 6G.<n>The discourse then transitions to a detailed exposition of the envisioned integration of AI within 6G networks.
  arXiv  Detail & Related papers  (2024-12-19T05:36:34Z)
• Socially Pertinent Robots in Gerontological Healthcare [81.67026771075037]
  This paper is an attempt to partially answer the question, via two waves of experiments with patients and companions in a day-care gerontological facility in Paris with a full-sized humanoid robot endowed with social and conversational interaction capabilities.<n>Overall, the users are receptive to this technology, especially when the robot perception and action skills are robust to environmental clutter and flexible to handle a plethora of different interactions.
  arXiv  Detail & Related papers  (2024-04-11T08:43:37Z)
• RoboScript: Code Generation for Free-Form Manipulation Tasks across Real and Simulation [77.41969287400977]
  This paper presents textbfRobotScript, a platform for a deployable robot manipulation pipeline powered by code generation. We also present a benchmark for a code generation benchmark for robot manipulation tasks in free-form natural language. We demonstrate the adaptability of our code generation framework across multiple robot embodiments, including the Franka and UR5 robot arms.
  arXiv  Detail & Related papers  (2024-02-22T15:12:00Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.