Overview

Robot state estimation combines sensor readings and models to infer quantities such as position, orientation, velocity, contact, and robot shape, which are needed for navigation and control. Common approaches include Kalman and invariant filters, particle filters, factor graphs and smoothing, and continuous-time methods that fuse asynchronous measurements from IMUs, cameras, LiDAR, radar, GNSS, encoders, and contact sensors. Learning-based methods increasingly complement these estimators by predicting motion, sensor reliability, or contact confidence, especially for legged robots and in degraded sensing conditions. A central challenge is maintaining accurate, consistent uncertainty estimates when contacts slip, sensors fail or arrive late, and the environment provides weak geometric information, without exceeding real-time computational limits.

Latest papers

CardsList

200 papers26 papers in the last four weeks, down 4% on the four weeks before. 0.2% of all new papers.

  1. RESPLE2: Inertial-Informed Recursive Non-Uniform Spline Estimation for Multi-Sensor Odometry with Global Refinement

    Oct 27, 2026Ziyu Cao, William Talbot, Song Li +4Robot State EstimationMultimodal Sensor Fusion

  2. State estimation for a hybrid rigid-continuum space manipulator system

    Oct 27, 2026Lorenzo Ticozzi, Patricio A. Vela, Panagiotis TsiotrasRobot State EstimationSpace Robotics

  3. Camera-to-Quadruped Robot Pose Estimation from Sequential Images

    Oct 27, 2026Seobin Hwang, Ji-Seong Beom, Yeong-Jun ChoRobot State EstimationRobotic Perception

  4. SVIn+: Multi-Modal Framework for Robust Underwater State Estimation using 3D Sonar, Visual-Inertial, Water-Pressure, and DVL

    Oct 27, 2026Chinmay Burgul, Xiaoming Zhao, Yewei Huang +4Robot State EstimationUnderwater Robotics

  5. Tilt-Rotor Quadcopter with Learned Residual Control and Mode-Dependent State Estimation

    Oct 22, 2026Ninad Joshi, Prabhat KumarQuadrotor ControlFeedback Control

  6. In-Context Learning World Models for Robot Dual-Arm Manipulation of Soft Garment with Partial Observations

    Oct 22, 2026Hengyi Sim, Quentin Rouxel, Dennis Hong +2World Models for RoboticsRobotic Manipulation

  7. RoPE-Flow: Monocular Vision-based Robot Pose Estimation via 2D Graph-Conditioned 3D Flow Matching

    Oct 15, 2026Liangjing Shao, Wanhao Liu, Zhiwei Fang +6Robot State EstimationRobotic Perception

  8. A Response to the Reply Presented in "A Fair Comparison of Sliding-Mode and Immersion-and-Invariance Observers"

    Oct 14, 2026Luis Cervantes-Pérez, Víctor Santibáñez, Jesús Sandoval +2Sliding Mode ControlAdaptive Control

  9. Navigation by Skylight Polarization via Rayleigh Model Optimization on a Road Vehicle

    Oct 14, 2026Ben Potter, Eslam Mounier, Aboelmagd Noureldin +2Robot NavigationRobot State Estimation

  10. RingNav: Task-Shaped Circular Memory for Visual Heading

    Oct 13, 2026Naitri Rajyaguru, Aryan Tajne, Stephen Jardim +2Robot NavigationRobot State Estimation

  11. Contractor Filters

    Oct 13, 2026Simon RohouRobot State EstimationRobust Estimation

  12. MSC: Multi-Stage Caster-aware Control Framework with Uncertainty-Aware NMPC and RL-based Execution Layer

    Oct 12, 2026Jinho Park, Jeongtae Lee, Jeonghyeok Lim +2Robot Trajectory TrackingNonlinear MPC

  13. Global Optimality of Pose Graph Optimization

    Oct 10, 2026Shuan Ding, Ruishuang Chen, Mengfan Cao +1Pose Graph OptimizationRobotic Optimization

  14. RAGNAROK: Radar-Aided Gravity-Normalized Alignment for Robust Open Keyframe-based Radar-Visual-Kinematic-Inertial SLAM

    Oct 8, 2026Hanjun Kim, Chiyun Noh, Sangwoo Jung +5Simultaneous Localization and MappingRobot State Estimation

  15. Belief-Space Planning with Planner-Conditioned Estimator Error under Intermittent Observations

    Oct 6, 2026Peter M. Donley, Joseph L. MooreBelief-Space PlanningRobot State Estimation

  16. Embedded Bare-Metal Radar-Inertial Odometry

    Oct 5, 2026Nicolai Adil Øyen Aatif, Morten Nissov, Kostas AlexisUAV NavigationRadar-Inertial Odometry

  17. Block Disentanglement in CRL: Bridging Identifiability and Visual State Estimation

    Oct 5, 2026Emre Acartürk, Pranamya Kulkarni, Puranjay Datta +3Causal Representation LearningCausal Identifiability

  18. GR-LIO: A Local Ground-Aware LiDAR-Inertial Odometry System Using Body-to-Ground Height

    Oct 4, 2026Zhixin Zhang, Yang Song, Liang Zhao +3LiDAR OdometryRobot State Estimation

  19. Who Went Where When on the Lunar Surface: Forensic Trajectory Analysis to Identify Byzantine Rovers

    Oct 2, 2026Lachlan Holden, Feras Dayoub, Melissa de Zwart +2Trajectory InferenceRobot State Estimation

  20. Towards Agile Vision-Based Multi-UAV Flight: Revisiting State Estimation

    Sep 30, 2026Michal Pliska, Matouš Vrba, Ondřej Víta +3Aerial RoboticsKalman Filtering

  21. Benchmarking EMlog Calibration for Autonomous Surface Vehicles

    Sep 30, 2026Samuel Cohen-Salmon, Itzik KleinModel CalibrationRobot State Estimation

  22. LBDU-VIO: Learned Bias Dynamics and Uncertainty for Visual-Inertial Odometry with Unreliable Vision

    Sep 30, 2026Qizhi Guo, Junning Lyu, Defu Lin +1Kalman FilteringVisual-Inertial Odometry

  23. Observability Analysis and Online Calibration of Visual-Inertial-Wheel Odometry for 4WIS4WID Mobile Robots

    Sep 29, 2026Branimir Ćaran, Vladimir Milić, Bojan Šekoranja +1Visual-Inertial OdometryRobot State Estimation

  24. A QCQP-Representable IMU Pre-Integration Factor for Certifiable State Estimation

    Sep 29, 2026Utkarsh Rai, Zhexin Xu, Bang-Shien Chen +1Constrained OptimizationRobot State Estimation

  25. Speed in the Blind Spot: An Interpretability Analysis of Dynamic Perception in VLMs for Autonomous Driving

    Sep 29, 2026Katharina Winter, Stefan Englmeier, Fabian B. FlohrVLMs for Autonomous DrivingVLM Interpretability

  26. Natural State-Prediction Accuracy can Hide Weak Controlled Responsiveness in VLA Readouts

    Sep 28, 2026Hyungjoon Kim, Wonbin Son, Mi Young Lee +2Robotic Policy EvaluationVision-Language-Action Models