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6 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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Latest papers 28

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Optical-Flow Wingbeat Counting in MuJoCo: A Comparison of Convolutional, Spiking, and Attention-Based Temporal Models
Sep 15, 2026Zhang NengboOptical Flow Temporal Convolutional Networks
School of Aerospace Engineering, Engineering Campus Universiti Sains Malaysia, 14300 Nibong Tebal, Pulau Pinang, Malaysia
Waggle Dance Inspired Motion Communication for Multiple UAVs in MuJoCo
Sep 15, 2026Zhang NengboMujoco Unmanned Aerial Vehicles
School of Aerospace Engineering, Engineering Campus Universiti Sains Malaysia, 14300 Nibong Tebal, Pulau Pinang, Malaysia
Admissable: Training Reinforcement Learning Agents against Adversarial Missingness
Sep 14, 2026Paul Stahlhofen, Luca Hermes, Tim Kochs +2Adversarial Training Offline Reinforcement Learning
Bielefeld University
Ostrich: Taking Large Strides Through Stiff Contact in Differentiable Dynamics
Sep 8, 2026Aleš Kučera, Karel ZimmermannRigid-Body Dynamics Differentiable Physics
Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
mjorbit: A Simulation Framework for Space Robotics
Sep 7, 2026John Z. Zhang, Joris Verhagen, Fausto Vega +2Mujoco Multi-Robot Systems
Department of Aeronautics and Astronautics, Massachusetts Institute of Technology · Division of Robotics, Perception and Learning, KTH Royal Institute of Technology
Real-Time Dynamics-Based Torque-Sampling MPPI for Compliant and Force Aware Manipulation
Sep 2, 2026Euncheol Im, Taehyun Kim, Yonghwan Oh +2Model Predictive Path Integral Torque
The Center for Humanoid Research, Korea Institute of Science and Technology (KIST), 02792 Seoul, South Korea · The School of Electrical Engineering, Korea University, 02841 Seoul, South Korea
Multi-modal Interactive Control of Robotic Arm based on Offline Large Language Models
Aug 8, 2026Hanxiao ChenMujoco Socratic Dialogue
Department of Electrical Engineering and Information Systems, University of Tokyo, Tokyo, Japan
SoRoMoX: Fast, Differentiable, and Parallelizable Soft Robot Models
Aug 6, 2026Maximilian Stölzle, Solange Gribonval, Daniel Feliu-Talegon +9Soft Robotics Cosserat Rod Theory
Delft University of Technology, Delft, The Netherlands · Italian Institute of Technology, Genoa, Italy · Massachusetts Institute of Technology, Cambridge, MA, USA +1
Learning Reach-Avoid Task with Reinforcement Learning: Vectorized Simulation and Benchmark
Jul 17, 2026Jonas Weihing, Shahram EivaziMujoco
*Tübingen university
TurboMPC: Fast, Scalable, and Differentiable Model Predictive Control on the GPU
Jun 23, 2026Gabriel Bravo-Palacios, Jianghan Zhang, Zachary Pestrikov +2Model Predictive Control Mujoco
Dartmouth College, Hanover, NH, USA · Toyota Research Institute, Los Altos, CA, USA
Real-World Deployment of Massively Parallel Sampling-Based MPC for Contact-Rich Manipulation
Jun 16, 2026Magnus Dierking, Joao Carvalho, An Thai Le +2Mujoco Robotic Manipulator
Intelligent Autonomous Systems Lab, TU Darmstadt, Germany · Interactive Robot Perception & Learning Lab, TU Darmstadt, Germany · German Research Center for AI (DFKI) +2
Interaction Dynamics for Dexterous Manipulation
Jun 12, 2026Yongyan CaoDexterous Manipulation Torque
Y. Cao is with Voryx Robotic LLC, San Jose, CA 95136, USA
MuJoCo-Drones-Gym: A GPU-Accelerated Multi-Drone Simulator for Control and Reinforcement Learning
Jun 6, 2026Manan TayalMujoco Aerial Robots
TAU-Intelligence
MobileGym: A Verifiable and Highly Parallel Simulation Platform for Mobile GUI Agent Research
May 25, 2026Dingbang Wu, Rui Hao, Haiyang Wang +8Skillgym Simulation-Based Reinforcement Learning
Institute of Automation, Chinese Academy of Sciences · Peking University · The Chinese University of Hong Kong
Dynamic Neural Koopman Distillation for Real-Time Robot Control Using Diffusion Models
May 24, 2026Lei Zheng, Peiqi Yu, Zengqi Peng +2Diffusion Policies Mujoco
Department of Electrical and Computer Engineering, National University of Singapore, Singapore · Department of Electrical and Computer Engineering, Carnegie Mellon University, USA · Robotics and Autonomous Systems Thrust, The Hong Kong University of Science and Technology, Hong Kong SAR, China
MuJoCoUni:Persistent Batched Runtime Primitives for MuJoCo
May 24, 2026Yufei Jia, Junzhe WuMujoco Runtime
Tsinghua University
Streaming Reinforcement Learning under Partial Observability with Real-Time Recurrent Learning
May 23, 2026Noah Farr, Aryaman Reddi, Carlo D'Eramo +1Recurrent Neural Networks Deterministic Replay
Technical University of Darmstadt · Zuse School ELIZA · Center for Artificial Intelligence and Data Science, University of Würzburg +1
MyoChallenge 2025: A New Benchmark for Human Athletic Intelligence
May 15, 2026Cheryl Wang, Chun Kwang Tan, Balint K. Hodossy +21Athleticism Biomechanics
1McGill University, Canada · 2National University of Singapore, Singapore · Imperial College London, UK +10
Real-Time Whole-Body Teleoperation of a Humanoid Robot Using IMU-Based Motion Capture with Sim2Sim and Sim2Real Validation
May 12, 2026Hamza Ahmed Durrani, Suleman KhanTeleoperation Sim-To-Real Gap
WeGo Robotics
JODA: Composable Joint Dynamics for Articulated Objects
May 11, 2026Tianhong Gao, Cheng Yu, Yinghao Xu +1Articulated Objects Kinematics
Peking University · Ant Group, Robbyant
PhySPRING: Structure-Preserving Reduction of Physics-Informed Twins via GNN
May 8, 2026Yixiong Jing, Xingyuan Chen, Guangming Wang +3Digital Twins Physics Simulation
University of Cambridge · Shanghai Jiao Tong University
PISTO: Proximal Inference for Stochastic Trajectory Optimization
May 8, 2026Hongzhe Yu, Zinuo Chang, Yongxin ChenRobust Trajectory Stochastic Optimization
School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA · School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
Sampling-Based MuJoCo MPC for Double-Pendulum Sway Suppression on a Shipboard Crane
Mar 17, 2026Oscar Pang, Lisa Coiffard, Paul Templier +3Model Predictive Control Inverted Pendulum
Adaptive and Intelligent Robotics Lab, Department of Computing, Imperial College London, Exhibition Rd, London, SW7 2BX, United Kingdom
Bridging the Sim-to-Real Gap with multipanda_ros2: A Real-Time ROS2 Framework for Multimanual Systems
Feb 2, 2026Jon Škerlj, Seongjin Bien, Abdeldjallil Naceri +1Mujoco Multi-Robot Systems
Munich Institute of Robotics and Machine Intelligence (MIRMI), Technische Universität München (TUM), Germany · Technische Universität Nürnberg (UTN), Germany · Mohamed Bin Zayed University of Artificial Intelligence, UAE
Robust and Efficient MuJoCo-based Model Predictive Control via Web of Affine Spaces Derivatives
Dec 24, 2025Chen Liang, Daniel RakitaModel Predictive Control Mujoco
Department of Computer Science, Yale University, New Haven, CT 06520, USA
Debate2Create: Robot Co-design via Multi-Agent LLM Debate
Oct 29, 2025Kevin Qiu, Marek CyganMulti-Agent Debate Multi-Agent Large Language Model Systems
University of Warsaw · 2IDEAS NCBR · 3Nomagic
Adaptive Reinforcement Learning for Unobservable Random Delays
Jun 17, 2025John Wikman, Alexandre Proutiere, David BromanOffline Reinforcement Learning Mujoco
EECS and Digital Futures, KTH Royal Institute of Technology, Stockholm, Sweden.
MuJoCable: Reduced-Order Surface-Routed Cable Transmission for Tendon-Driven Robots
Date pendingYi Zhang, Qi Shao, Yicong Lin +3Mujoco Wiring

Sep 15, 2026, cs.CVJ/K move · Enter open · S save

Optical-Flow Wingbeat Counting in MuJoCo: A Comparison of Convolutional, Spiking, and Attention-Based Temporal Models

Zhang Nengbo

School of Aerospace Engineering, Engineering Campus Universiti Sains Malaysia, 14300 Nibong Tebal, Pulau Pinang, Malaysia

Optical Flow Temporal Convolutional Networks Rotorcraft Counting Motion-Based Perception Convolutional+3

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Visual monitoring of flapping-wing vehicles requires distinguishing individual wingbeats from motion strength and average frequency. This paper presents a controlled MuJoCo evaluation of wingbeat counting from signed optical flow observed by virtual cameras mounted on Crazyflie vehicles. Three flapping-wing models were recorded at optical distances of 1.5 and 3.0 m, producing 1,440 clips from 240 paired scene configurations with a scene-level 3:1 training-test split. A common spatial convolutional encoder was combined with a causal temporal convolutional network, a recurrent leaky integrate-and-fire spiking network, or causal self-attention. Each model predicted phase and activity, followed by the same directed-crossing event counter. The six existing convolutional models were retained, and all twelve new models were frozen before their test predictions were generated. Exact-count accuracies at 1.5 m were 96.67%, 95.00%, and 96.67%, respectively; at 3.0 m they were 94.44%, 92.22%, and 95.00%. All paired scene-bootstrap intervals for differences in exact-count accuracy included zero. Seven far-distance spiking-model clips had correct totals despite event-timing mismatches, demonstrating why total-count and event-level measurements must be reported together. The results support the feasibility of causal optical-flow counting in the tested setting and identify boundary-sensitive errors. They do not establish an architecture ranking across repeated training, real-flight robustness, or hardware efficiency.

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