83 skills found · Page 1 of 3
facebookresearch / VideoPose3DEfficient 3D human pose estimation in video using 2D keypoint trajectories
JokerJohn / PALoc[TMECH'2024] PALoc: Advancing SLAM Benchmarking with Prior-Assisted 6-DoF Trajectory Generation and Uncertainty Estimation
APRIL-ZJU / Clins[IROS 2021] CLINS: Continuous-Time Trajectory Estimation for LiDAR-Inertial System
aras62 / PIEPredictPIE: A Large-Scale Dataset and Models for Pedestrian Intention Estimation and Trajectory Prediction
adrelino / Interpolation MethodsSurvey of Higher Order Rigid Body Motion Interpolation Methods for Keyframe Animation and Continuous-Time Trajectory Estimation
lamfur07 / Flight Dynamics And Control UAVsUnderstanding of flight control systems, including dynamic models for UAVs, low level autopilot design, trajectory following, and path planning. The essential physics and sensors of UAV problems, including low-level autopilot for stability and higher-level autopilot functions of path planning will be explored. Rigid-body dynamics through aerodynamics, stability augmentation, and state estimation using onboard sensors, to maneuvering through obstacles. Files include simulation projects using the MATLAB/Simulink environment. Projects start from modeling rigid-body dynamics, then add aerodynamics and sensor models. Furthermore, low-level autopilot code, extended Kalman filters for state estimation, path-following routines, and high-level path-planning algorithms.
CogRob / Distributed MapperThis library is an implementation of the algorithm described in Distributed Trajectory Estimation with Privacy and Communication Constraints: a Two-Stage Distributed Gauss-Seidel Approach.
utiasASRL / SteamThe Simultaneous Trajectory Estimation and Mapping (STEAM) Engine.
DSL-Lab / MoFlow[CVPR 2025] MoFlow: One-Step Flow Matching for Human Trajectory Forecasting via Implicit Maximum Likelihood Estimation Distillation
abduallahmohamed / Social ImplicitCode for: "Social-Implicit: Rethinking Trajectory Prediction Evaluation and The Effectiveness of Implicit Maximum Likelihood Estimation" Accepted @ ECCV2022
facebookresearch / Visual Inertial Bundle AdjustmentVisual-inertial optimization of VIO trajectories and SLAM maps via accurate sensor modelling, with imu pre-integrated terms, full re-estimation of intrinsics/extrinsics on a generic rig and modelling of rolling shutter cameras.
RCL-NUS / NeuroMHENeural Moving Horizon Estimation (NeuroMHE) is an auto-tuning and adaptive optimal estimator. It fuses a nueral network with an MHE to render fast online adaptation to state-dependent noise. The neural network can be efficiently trained from the robot's trajectory tracking errors without the need for the ground truth data.
meaten / FlowChain ICCV2023Trajectory prediction method using a stacked normalizing flow for fast and accurate density estimation.
gtrll / PiperNo description available
codac-team / CodacCodac (Catalog Of Domains And Contractors) is a C++/Python/Matlab library providing tools for interval computations and constraint programming over real numbers, trajectories and sets. It has numerous applications in parameter estimation, guaranteed integration, robot localization, and provides reliable outputs.
jasleon / Visual OdometryThis project implements visual odometry to estimate the trajectory of a self-driving car.
jiahaoLjh / Trajectory Pose 3dTrajectory Space Factorization for Deep Video-Based 3D Human Pose Estimation
againerju / JooduJoint Out-of-Distribution Detection and Uncertainty Estimation for Trajectory Prediction: Model, training and evaluation code.
XinyanGT / Online Gpslam CodeCode for the paper "Incremental Sparse GP Regression for Continuous-time Trajectory Estimation and Mapping"
frank1ma / DDRTC Of UMSsThis paper presents a data-driven control design framework to achieve robust tracking control without exploiting mathematical model of nonlinear underactuated mechanical systems (UMS). The method leverages the differential flatness property of linearized systems and online estimation and compensation of disturbances by active disturbance rejection control (ADRC). The differentially flat output is derived directly from measured data with unknown dynamics and parameters of UMS by the flat output identification (FOID) algorithm. A reduced nominal model of UMS is proposed to simplify the process of finding flat output and trajectory planning. Technique of sparse regression is applied to identify the relationships between flat output and system states, which reduces the order of the well-known extended state observer (ESO) and thereby make the ESO more effective for both trajectory planning and tracking in terms …
