This paper provides an overview of evolutionary robotics techniques applied to on-line distributed evolution for robot collectives -- namely, embodied evolution. It provides a definition of embodied evolution as well as a thorough description of the underlying concepts and mechanisms. The paper also presents a comprehensive summary of research published in the field since its inception (1999-2017), providing various perspectives to identify the major trends. In particular, we identify a shift from considering embodied evolution as a parallel search method within small robot collectives (fewer than 10 robots) to embodied evolution as an on-line distributed learning method for designing collective behaviours in swarm-like collectives. The paper concludes with a discussion of applications and open questions, providing a milestone for past and an inspiration for future research.
University of Bremen（不来梅大学）；Örebro University（厄勒布鲁大学）
We present a commonsense, qualitative model for the semantic grounding of embodied visuo-spatial and locomotive interactions. The key contribution is an integrative methodology combining low-level visual processing with high-level, human-centred representations of space and motion rooted in artificial intelligence. We demonstrate practical applicability with examples involving object interactions, and indoor movement.
Learning Primitive Embodied World Models: Towards Scalable Robotic Learning
Shanghai AI Lab（上海人工智能实验室）；Fudan（复旦大学）；SJTU（上海交通大学）；NJUST（南京理工大学）；THU（清华大学）；Harvard（哈佛大学）；ZJU（浙江大学）；NJU（南京大学）；USTC（中国科学技术大学）；Tongji（同济大学）；HKUST (GZ)（香港科技大学（广州））
University of Trieste（的里雅斯特大学）；Oslo Metropolitan University（奥斯陆城市大学）
Voxel-based Soft Robots (VSRs) are a form of modular soft robots, composed of several deformable cubes, i.e., voxels. Each VSR is thus an ensemble of simple agents, namely the voxels, which must cooperate to give rise to the overall VSR behavior. Within this paradigm, collective intelligence plays a key role in enabling the emerge of coordination, as each voxel is independently controlled, exploiting only the local sensory information together with some knowledge passed from its direct neighbors (distributed or collective control). In this work, we propose a novel form of collective control, i…
A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI
Department of Computer Science, City University of Hong Kong（城市大学计算机科学系）；School of Electrical and Electronic Engineering, Nanyang Technological University（南洋理工大学电子与电气工程学院）；Department of Informatics, Universität Hamburg（汉堡大学信息学院）
Roborobo! is a multi-platform, highly portable, robot simulator for large-scale collective robotics experiments. Roborobo! is coded in C++, and follows the KISS guideline ("Keep it simple"). Therefore, its external dependency is solely limited to the widely available SDL library for fast 2D Graphics. Roborobo! is based on a Khepera/ePuck model. It is targeted for fast single and multi-robots simulation, and has already been used in more than a dozen published research mainly concerned with evolutionary swarm robotics, including environment-driven self-adaptation and distributed evolutionary op…
Safe Embodied AI for Long-horizon Tasks: A Cross-layer Analysis of Robotic Manipulation
UNIST InnoCORE AI-Space Solar Initiative（UNIST创新核心人工智能空间太阳能计划）；Ulsan National Institute of Science and Technology (UNIST)（乌山国立科学技术研究院）；Automation and Systems Research Institute（自动化与系统研究所）；Department of Electrical and Computer Engineering（电气与计算机工程系）；Interdisciplinary Program in Artificial Intelligence（人工智能跨学科项目）；LG Electronics（LG电子）
We introduce ROS-X-Habitat, a software interface that bridges the AI Habitat platform for embodied learning-based agents with other robotics resources via ROS. This interface not only offers standardized communication protocols between embodied agents and simulators, but also enables physically and photorealistic simulation that benefits the training and/or testing of vision-based embodied agents. With this interface, roboticists can evaluate their own Habitat RL agents in another ROS-based simulator or use Habitat Sim v2 as the test bed for their own robotic algorithms. Through in silico expe…
Guava: Distilling Frontier VLMs into a Compact Agent through a Robotic Manipulation Harness
University of Maryland College Park（马里兰大学帕克分校）；University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；University of Waterloo（滑铁卢大学）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；University of Pennsylvania（宾夕法尼亚大学）；Amazon FAR（亚马逊 FAR）
LLM-Empowered Embodied Agent for Memory-Augmented Task Planning in Household Robotics
Automation and Control Institute, Faculty of Electrical Engineering, TU Wien（自动化与控制研究所，电气工程学院，维也纳技术大学）；AIT Austrian Institute of Technology GmbH, Center for Vision, Automation and Control（奥地利技术研究所（AIT）有限公司，视觉、自动化与控制中心）
Pipette: An Embodied Simulation Platform, Benchmark, and Data-Efficient Augmentation Framework for Wet-Lab Robotics
Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education（能源化工过程智能制造国家重点实验室）；Department of Computer Science and Engineering（计算机科学与工程系）；Department of Laboratory Medicine（实验室医学系）；Shanghai Jiao Tong University School of Medicine（上海交通大学医学院）
Transforming Surgical Interventions with Embodied Intelligence for Ultrasound Robotics
Centre for Artificial Intelligence and Robotics (CAIR), HKISI-CAS（香港中文大学（深圳）人工智能与机器人中心（HKISI-CAS））；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）
E-TTS: A New Embodied Test-Time Scaling Framework for Robotic Manipulation
New Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所模式识别国家重点实验室）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；Foundation Model Research Center, Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所基础模型研究中心）；FiveAges（五时代）
ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI
University of California San Diego（加州大学圣地亚哥分校）；Carnegie Mellon University（卡内基梅隆大学）；Hillbot（Hillbot公司）；TU Dresden（德累斯顿技术大学）；Tsinghua University（清华大学）；King’s College London（伦敦国王学院）
A large body of compelling evidence has been accumulated demonstrating that embodiment - the agent's physical setup, including its shape, materials, sensors and actuators - is constitutive for any form of cognition and as a consequence, models of cognition need to be embodied. In contrast to methods from empirical sciences to study cognition, robots can be freely manipulated and virtually all key variables of their embodiment and control programs can be systematically varied. As such, they provide an extremely powerful tool of investigation. We present a robotic bottom-up or developmental appr…
Never-Ending Behavior-Cloning Agent for Robotic Manipulation
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences（机器人国家重点实验室，沈阳自动化研究所，中国科学院）；University of Chinese Academy of Sciences（中国科学院大学）；School of Automation Science and Engineering, South China University of Technology（自动化科学与工程学院，华南理工大学）；Mohamed bin Zayed University of Artificial Intelligence（马斯达尔大学人工智能学院）
EnvBridge: Bridging Diverse Environments with Cross-Environment Knowledge Transfer for Embodied AI
Panasonic Connect Co., Ltd.（松下连接有限公司）；National University of Singapore（新加坡国立大学）；Panasonic R&D Center Singapore（松下新加坡研发中心）；Panasonic R&D Center Germany（松下德国研发中心）
Ritsumeikan University（立命馆大学）；The University of Electro-Communications（电气通信大学）；Okayama Prefectural University（冈山县立大学）；Waseda University（早稻田大学）；National Institute of Advanced Industrial Science and Technology（产业技术综合研究所）
Humans can learn the use of language through physical interaction with their environment and semiotic communication with other people. It is very important to obtain a computational understanding of how humans can form a symbol system and obtain semiotic skills through their autonomous mental development. Recently, many studies have been conducted on the construction of robotic systems and machine-learning methods that can learn the use of language through embodied multimodal interaction with their environment and other systems. Understanding human social interactions and developing a robot th…
Advances and Innovations in the Multi-Agent Robotic System (MARS) Challenge
SJTU（上海交通大学）；Oxford（牛津大学）；USTC（中国科学技术大学）；Shanghai AI Lab（上海人工智能实验室）；CMU（卡内基梅隆大学）；HKU（香港大学）；Tongji（同济大学）；UC San Diego（南加州大学）；CUHK-SZ（香港中文大学（深圳））；SYSU（华南理工大学）；Harvard（哈佛大学）
Blockchain Infrastructure for Intelligent Cyber--Physical--Social Systems:Post-Quantum Security, Interoperability, and Trustworthy Data Economies in the Era of Embodied AI
Hong Kong University of Science and Technology（香港理工大学）；Sun Yat-sen University（中山大学）；Amazon Web Services（亚马逊网络服务）；Duke Kunshan University（杜克昆山大学）
FZI Research Center For Information Technology（FZI信息技术研究中心）；University of California Irvine（加州大学欧文分校）
Spike-based communication between biological neurons is sparse and unreliable. This enables the brain to process visual information from the eyes efficiently. Taking inspiration from biology, artificial spiking neural networks coupled with silicon retinas attempt to model these computations. Recent findings in machine learning allowed the derivation of a family of powerful synaptic plasticity rules approximating backpropagation for spiking networks. Are these rules capable of processing real-world visual sensory data? In this paper, we evaluate the performance of Event-Driven Random Back-Propa…
