In this work, a spiking neural network (SNN) is proposed for approximating differential sensorimotor maps of robotic systems. The computed model is used as a local Jacobian-like projection that relates changes in sensor space to changes in motor space. The SNN consists of an input (sensory) layer and an output (motor) layer connected through plastic synapses, with inter-inhibitory connections at the output layer. Spiking neurons are modeled as Izhikevich neurons with a synaptic learning rule based on spike-timing-dependent plasticity. Feedback data from proprioceptive and exteroceptive sensors are encoded and fed into the input layer through a motor babbling process. As the main challenge to building an efficient SNN is to tune its parameters, we present an intuitive tuning method that considerably reduces the number of neurons and the amount of data required for training. Our proposed architecture represents a biologically plausible neural controller that is capable of handling noisy sensor readings to guide robot movements in real-time. Experimental results are presented to validate the control methodology with a vision-guided robot.
Spiking neural state machine for gait frequency entrainment in a flexible modular robot
University of California, Santa Cruz（加州大学圣克鲁兹分校）；Genomics Institute, University of California, Santa Cruz（加州大学圣克鲁兹分校基因组学研究所）；Howard Hughes Medical Institute（霍华德·休斯医学研究所）
Center of Data Science, New York University（纽约大学数据科学中心）；Center of Biomedical Engineering, Duke university（杜克大学生物医学工程中心）；Function Hub, The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州）功能枢纽）
Designing Behaviour in Bio-inspired Robots Using Associative Topologies of Spiking-Neural-Networks
The Open University（开放大学）
本研究探讨了设计和控制的代理和机器人的行为，使用简单的电路的尖峰神经元和尖峰时间依赖可塑性（STDP）作为一种机制的联想和无监督学习。基于“奖励和惩罚”的经典条件反射，它表明，这些机器人学会了识别和避免障碍，以及识别和寻找奖励刺激。使用仿真和编程环境NetLogo，开发了Integrate and Fire模型的软件引擎，该软件引擎允许我们以离散时间步长监控所提出的神经网络中每个单个神经元、突触和尖峰的动态。这些脉冲神经网络（SNN）充当实验机器人的简单大脑。乐高Mindstorms机器人套件用于模拟代理的实施例。在本文中的拓扑积木，以及再现实验所需的神经参数。本文总结了由此产生的行为以及观察到的动态的神经电路。附件载有与NetLogo代码的互联网连接。
A Spiking Central Pattern Generator for the control of a simulated lamprey robot running on SpiNNaker and Loihi neuromorphic boards
Technical University of Munich（慕尼黑工业大学）；fortiss - Research Institute of the Free State of Bavaria（巴伐利亚自由州fortiss研究所）；École Polytechnique Fédérale de Lausanne（洛桑联邦理工学院）；University of Waterloo（滑铁卢大学）
A Neurorobotic Embodiment for Exploring the Dynamical Interactions of a Spiking Cerebellar Model and a Robot Arm During Vision-based Manipulation Tasks
The Hong Kong Polytechnic University（香港理工大学）；Technical University of Denmark（丹麦技术大学）
Training slow silicon neurons to control extremely fast robots with spiking reinforcement learning
Institute of Neuroinformatics, UZH and ETH Zurich（神经信息研究所，苏黎世联邦理工学院和苏黎世联邦理工学院）；Istituto Italiano di Tecnologia（意大利技术研究所）；Technical University of Munich（慕尼黑技术大学）；Natl. Center for Radiation Protection and Computational Physics, Istituto Superiore di Sanità（辐射防护与计算物理国家中心，意大利卫生超级研究所）；Digital Society Initiative, University of Zurich（数字社会倡议，苏黎世大学）
Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation
eBRAIN Lab, Division of Engineering, New York University Abu Dhabi (NYUAD)（eBRAIN实验室，工程系，纽约大学阿布扎比分校）；Center for Quantum and Topological Systems (CQTS), NYUAD Research Institute（量子与拓扑系统中心（CQTS），NYUAD研究机构）
ES-Parkour: Advanced Robot Parkour with Bio-inspired Event Camera and Spiking Neural Network
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Beijing Innovation Center of Humanoid Robotics Co., Ltd.（北京人形机器人创新中心有限公司）；Zhejiang University（浙江大学）
Brain-inspired Action Generation with Spiking Transformer Diffusion Policy Model
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, CAS（中国科学院脑认知与脑智能技术重点实验室）；Center for Long-term Artificial Intelligence（长期人工智能中心）
Closed loop interactions between spiking neural network and robotic simulators based on MUSIC and ROS
Institute for Advanced Simulation (IAS-6), Theoretical Neuroscience（高等模拟研究所（IAS-6），理论神经科学）；Institute of Neuroscience and Medicine (INM-6), Computational and Systems Neuroscience（神经科学与医学研究所（INM-6），计算与系统神经科学）；JARA BRAIN Institute I（JARA BRAIN 研究所 I）；Jülich Research Center（于利希研究中心）；JARA Jülich（JARA 于利希）；PDC Center for High Performance Computing KTH Stockholm（KTH 斯德哥尔摩高性能计算中心）；Faculty of Biology Albert-Ludwig University of Freiburg（弗赖堡阿尔伯特-路德维希大学生物学院）；Bernstein Center Freiburg Albert-Ludwig University of Freiburg（弗赖堡阿尔伯特-路德维希大学伯恩斯坦中心）
Spiking Neural Network Control of a Flapping-Wing Robot on Resource-Constrained Hardware
Institute for AI Industry Research (AIR)（人工智能产业研究院）；Tsinghua University（清华大学）；Department of Computer Science and Technology（计算机科学与技术系）；Xinchen Qihang Inc.（新晨科技有限公司）
Spiking Neural-Invariant Kalman Fusion for Accurate Localization Using Low-Cost IMUs
Guangdong Institute of Intelligence Science and Technology（广东智能科学与技术研究院）；East China Normal University（东华大学）；Innovation and Research and Development Department, BoardWare Information System Co.Ltd（BoardWare信息系统有限公司创新与研发部）
Spiking Neural Networks for Continuous Control via End-to-End Model-Based Learning
Donders Centre for Cognition, Radboud University, Nijmegen, The Netherlands（鲁布·大学多纳中心，尼姆egen，荷兰）；Cajal Neuroscience Center, Spanish National Research Council, Madrid, Spain（西班牙国家科研 council Cajal 神经科学中心，马德里，西班牙）
Neuromorphic Spiking Ring Attractor for Proprioceptive Joint-State Estimation
1 Istituto Italiano di Tecnologia, Genoa, Italy, 2 Department of Neurosurgery, University Hospital Zürich, Switzerland 3 Institute of Neuroinformatics, Univ. of Zurich；ETH Zurich, Switzerland 4 DIEEI, University of Catania Catania, Italy, 5 IDLAB, University of Antwerp；AI \& Algorithms, imec, Leuven, Belgium 6 Digital Society Initiative, University of Zurich, Switzerland these authors contributed equally
A brain-inspired information fusion method for enhancing robot GPS outages navigation
Guangdong Institute of Intelligence Science and Technology（广东智能科学与技术研究院）；School of Electronic Engineering and Automation, Guilin University of Electronic Technology（桂林电子科技大学电子工程与自动化学院）；Innovation and Research and Development Department, BoardWare Information System Company Ltd（BoardWare信息系统公司创新与研发部）
