Robotics and Automated Systems

Últimos artículos

• Token Communication-Assisted Collaborative Embodied Artificial Intelligence: Concepts, Framework, and Opportunities

  Peng Yi, Ying-Chang Liang · 2 de octubre de 2026

  Collaborative embodied artificial intelligence (CEAI) enables multiple physical agents to perceive, reason, and act cooperatively in dynamic environments. Effective communication is essential for CEAI, yet CEAI agents must exchange not only large multimodal observations but also task-relevant insigh…

• AIMS: An Agentic AI Framework for Sim-to-Real Multi-Modal ISAC

  Yijie Bian, Kai Zhang, Wei Guo, Zixin Wang, Shenghui Song, Jun Zhang, Khaled B. Letaief · 1 de octubre de 2026

  Multi-modal integrated sensing and communication (ISAC) enables environmental perception and reliable connectivity for intelligent wireless networks. Data-driven multi-modal ISAC models depend heavily on annotated real-world data to learn relationships across sensing and wireless observations, there…

• Embodied Semantic Communication for Collective Autonomous Agents: A Tutorial on Representation, Wireless Delivery, and Closed-Loop Coordination

  Yizheng Huang, Wensheng Lin, Lixin Li, Qinghe Du, Wenchi Cheng, Zhu Han · 30 de septiembre de 2026

  As autonomous systems and embodied intelligence enter the dynamic physical world, multi-agent collaboration calls for a paradigm shift in communication design. However, existing communication paradigms overlook that agents form action understanding from their own states, environmental observations, …

• MemBodied: Recurrent Associative Memory for Vision-Language-Action Models

  Tej Deep Pala, Navonil Majumder, Bryce Goh, Raphael Yee, Jianfei Yang, Liming Chen, Soujanya Poria · 24 de septiembre de 2026

  Vision-Language-Action models provide a strong foundation for general-purpose robot control, yet a vast majority of policies do not preserve and leverage episode-level information beyond the current observation. This limitation is consequential in history-dependent manipulation tasks that depend on …

• OmniFysics-Nano-V2 Technical Report: Understanding the Physical World Across Modalities

  Yizhou Liu, Jinghang Han, Kaixiang Qiu, Qi He, Minghao Han, Yue Jiang, Xujia Chen, Wei Zou, Shunli Wang, Lihua Zhang, Dingkang Yang · 23 de septiembre de 2026

  Omni-modal models have expanded multimodal interaction across vision, audio, speech, and language. However, their training is predominantly organized around semantic descriptions and general-purpose objectives, leaving physical attributes, interaction states, and causal mechanisms only partially spe…

• AtomEgo: Exploring Ego-Robot Integration for Embodied Foundation Model Pretraining

  Di Wu, Dongchen Zheng, Junhe Sheng, Zhongxing Wei, Songxin Zhang, Zejian Xie, Xiaoquan Sun, Junyang Zheng, Zhuoyang Song, Jiaxing Zhang, Jiayu Chen · 21 de septiembre de 2026

  Embodied foundation models are constrained by the limited scale and diversity of robot demonstrations, motivating the use of large-scale egocentric human interaction data. However, how to effectively incorporate such data into embodied-model pre-training remains unclear because of substantial embodi…

• VLN on the Fly: An Onboard Vision-Language Navigation Stack for Aerial Robots

  Marco S. Tayar, Felipe Tommaselli, Gianluca Capezutto, Pedro Antonio Rabelo Saraiva, Pedro H. V. de Freitas, Lucas Kido, Guilherme Sonego, Ricardo V. Godoy, Marcelo Becker · 18 de septiembre de 2026

  Running vision-language navigation fully onboard an aerial robot is hard, since grounding, planning, and control must share limited compute and a single-stage error is difficult to isolate in flight. End-to-end aerial policies fuse these stages into one network, giving up the observability and safet…

• Efficient Vision-Language-Action Management and Serving for Robot Factories

  Dionysios Adamopoulos, Nattapol Chanpaisit, Basel Fakhri, Christina Giannoula · 14 de septiembre de 2026

  Vision-Language-Action (VLA) models show high robotic manipulation capabilities via a two-stage design: a Vision-Language Model (VLM) stage followed by an Action Diffusion Transformer (ADiT) stage. Since robots must meet strict Service-Level Objectives (SLOs) for safety, VLA inference is inherently …

• Pelican-Sim 1.0: A General World Model Simulator for Embodied Intelligence

  Shilong Zou, Shilin Zhang, Yingji Zhang, Yuhang Huang, Yi Zhang, Zeyuan Ding, Han Dong, Junwei Liao, Yong Dai, Jian Tang, Xiaozhu Ju · 14 de septiembre de 2026

  In this technical report, we propose Pelican-Sim 1.0, a general world model simulator for embodied intelligence that predicts future observations from visual context and robot actions to support downstream learning and decision making. The model incorporates four key design features: (1) Unified act…

• EMMI: Edge Multi-Modal Intelligence for Communication-Efficient MLLM Inference via Fused Representation Compression

  Motahare Mounesan, Irfan Khan · 11 de septiembre de 2026

  Recent advances in multimodal large language mod- els (MLLMs) have opened new opportunities for edge intelligence by enabling reasoning across heterogeneous sensor modalities, such as vision, text, and telemetry data. However, deploying these capabilities on resource-constrained edge platforms remai…

• Modality-Decoupled Federated Learning for Privacy-Preserving Embodied Intelligence in 6G

  Zhuodong Liu, Xiangyu Li, Chunhong Yuan, Hongyang Du, Bodong Shang, Qingqing Wu, Tony Q. S. Quek, Mohsen Guizani · 10 de septiembre de 2026

  Sixth-generation (6G) wireless networks are expected to provide a key infrastructure for large-scale embodied intelligence, where heterogeneous robots collaborate through low-latency connectivity, edge intelligence, and distributed sensing. Vision-language-action (VLA) models offer a foundation by i…

• MoEMB: Scaling Universal Multimodal Embeddings with Efficient Mixture-of-Experts Models

  Xuanming Cui, Shlok Kumar Mishra, Wentao Bao, Aashu Singh, Zihao Wang, Xiangjun Fan, Jun Xiao, Ser-Nam Lim, Jianpeng Cheng · 9 de septiembre de 2026

  Universal multimodal embedding (UME) increasingly demands encoder's capacity for handling a broad range of tasks and modalities with increased complexity. Prior scaling methods either increase the representation size, retrieval effort, or scales the encoder into a heavy multimodal LLM. Recent works,…

• MEMOBench: A Process Level Memory Benchmark for Robotic Manipulation

  Haiyang Sun, Haoxiao Wang, Junming Chen, Weicheng Fang, Zihao Su, Jingkun Yi, Wenyou Yi, Hao Chen, Zhou Zhao · 9 de septiembre de 2026

  Robotic manipulation often requires acting on information that is no longer visible, yet Vision-Language-Action policies are usually evaluated when the current observation largely determines the next action. Existing robotic memory benchmarks expose this gap, but they still rely mainly on final task…

• EmbodiedSkills: A Unified Framework for Orchestrating, Training, and Deploying VLA Agents

  Wei Wang, Wenqiao Zhang, Yutong Lin, Yuqian Yuan, Tianwei Lin, Jinhao Mao, Zhenxuan Fan, Mingjian Gao, Yang Dai, Wentong Li, Zheqi Lv, Zheng Dong, Yingjie Niu, Jiaqi Zhu, Jun Xiao, Chao Li, Yueting Zhuang · 2 de septiembre de 2026

  Vision-language-action (VLA) models map visual observations and language instructions directly to robot actions, but long-horizon tasks require more than action prediction. An agent must coordinate perception, planning, execution, progress verification, and recovery as the physical state evolves. An…

• Beyond Multimodal Alignment: Certifying Physical Language through Response Substitution and Ordered Execution

  Kaizhen Tan, Xin Xu, Siru Tao, Yixiao Li, Hanzhe Hong, Yang Feng, Heqing Du · 21 de agosto de 2026

  World models increasingly treat compact multimodal representations as interfaces between perception and physical interaction, yet existing probes do not establish whether different sensors carry the same executable meaning or whether that meaning survives a new action composition. We introduce an op…

• OrthoSkillVLA: Continual Skill Learning via Gradient-Informed Skill Subspace Adaptation

  Jiaqi Wang, Zhou Fang, Qiongfeng Shi, Yi Zhou · 21 de agosto de 2026

  Pretrained Vision-Language-Action models provide a strong foundation for robot learning, but sequentially adapting them to diverse skills can perturb the representations and velocity mappings used by previous skills, leading to catastrophic forgetting. Architecture-based approaches improve retention…

• Context Aware AI Assistant and AR Interface for Lunar Extravehicular Activity (EVA) Procedural Guidance

  Rodrigo Gallardo, Qilmeg Doudatcz, Ganit Goldstein, Ilkyaz Sarimehmetoglu, Sergio Mutis, Alexander Htet Kyaw, Anita Lin, Clara Emmerling, Berfin Ataman, Skylar Tibbits · 17 de agosto de 2026

  As human space exploration returns to the Moon, astronauts need rapid access to procedural information during extravehicular activities (EVAs), where attention is divided across navigation, repair tasks, tool handling, and environmental risk. The challenge is not the absence of information, but surf…

• CEAA: A Cognitive Embodied Agents Architecture for Interactive Computing Systems

  Aimilios Hadjiliasi, Louis Nisiotis · 11 de agosto de 2026

  The development of embodied Intelligent Virtual Agents (IVAs) that have cognitive capabilities in real-time interactive virtual environments remains a challenge, even with today's advancements in technology. Existing architectures are often focused on either the implementation of low-level reactive …

• Lingjing: A Simulation Testbed for Multi-Agent Embodied Tasks in Open-Ended Cities

  Xiaohe Li, Yiru Wang, Junhao Fan, Mingyuan Liu, Jie Huang, Kaixin Zhang, Jiahao Li, Chen Qian, Zide Fan · 11 de agosto de 2026

  Urban embodied intelligence requires coordination among heterogeneous agents (e.g., UAVs, ground robots, and autonomous vehicles) in dynamic cities. Simulators therefore provide a scalable foundation for developing and evaluating such coordination. Existing platforms nevertheless isolate different e…

• GAUGE: A Measurement-Grounded Benchmark for Physical Fidelity in Simulation Engines and Video World Models

  Shuai Wang, Yaxin Feng, Xuekun Jiang, Shihan Tian, Ningyu Yan, Xing Shen, Chaoyang Lyu, Hui Wang, Yunsong Zhou, Hanqing Wang, Jiangmiao Pang, Yang Xiang, Xing Gao, Chunhua Shen, Weinan Zhang · 7 de agosto de 2026

  Physics engines facilitate large-scale training and evaluation for embodied intelligence, while generative video world models are emerging as implicit simulators of future states and interactions. However, existing evaluations of physical fidelity are often conducted in isolation and rely heavily on…

• PhyAI: Real-Time Physical AI at the Edge, Scalable Rollouts in the Cloud

  Chenghua Wang, Daliang Xu, Dongqi Cai, Duojin Sun, Hao Zhang, Haoze Qian, Huaiyuan Zhang, Jinshuo Cui, Junbo Cui, Kezhao Zhao, Longxi Gao, Mengwei Xu, Rongjie Yi, Tam Sikyuen, Tianyue Zhang, Weikai Xie, Xuanzhe Liu, Yingying Qin, Yiwen Lu, Yuan Yao, Yuezhi Zu, Yunhan Guo, Yuxin Zheng, Ziqi Guo · 6 de agosto de 2026

  Physical AI policies require inference throughout their lifecycle, including model evaluation, cloud reinforcement learning rollout, edge GPU serving, and onboard deployment. Although these settings share the same checkpoint and action semantics, they often rely on separate inference programs. To un…

• Metis: Memory Foundation Model

  Zeyu Zhang, Ziliang Guo, Yihang Sun, Xichong Zhang, Xixuan Hao, Zehao Lin, Yang Zhang, Xiaoyan Zhao, Tong Shen, Bo Tang, Zhi-Qin John Xu, Junchi Yan, Haofen Wang, Xu Chen, Feiyu Xiong, Zhiyu Li, Tat-Seng Chua · 30 de julio de 2026

  Recent advances in AI agents have increasingly internalized native capabilities into their underlying foundation models, giving rise to multimodal foundation models and large reasoning models. However, agent memory is still primarily implemented through external modules, leaving the native memory ca…

• Agentic IoT: Architectures, Applications, and Challenges Toward the Internet of Agents

  R\"umeysa Hilal Sevin\c{c}, Bahaeddin T\"urko\u{g}lu, \.Ibrahim K\"ok · 7 de julio de 2026

  The integration of AI into Internet of Things (AIoT) systems has gradually transformed them from passive data collection infrastructures into intelligent systems capable of anomaly detection, predictive maintenance, classification, forecasting, and optimization. However, most existing solutions stil…

• Metacognitive Myopia in Large Language Models

  Florian Scholten, Tobias R. Rebholz, Mandy H\"utter · 16 de junio de 2026

  Large Language Models (LLMs) exhibit potentially harmful biases that reinforce culturally embedded stereotypes, influence moral judgments, or amplify positive evaluations of majority groups. We propose metacognitive myopia as a cognitive-ecological framework accounting for a conglomerate of establis…

• A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI

  Lik Hang Kenny Wong, Xueyang Kang, Kaixin Bai, Jianwei Zhang · 10 de junio de 2026

  Navigation and manipulation are core capabilities in Embodied AI, but training agents to perform them directly in the real world is costly, time-consuming, and unsafe. Therefore, sim-to-real transfer has emerged as a key approach, yet the sim-to-real gap persists. This survey examines how physics si…