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Found 13 papers, 11 papers with code
Contact-Aided Invariant Extended Kalman Filtering for Legged Robot State Estimation
On the basis of the theory of invariant observer design by Barrau and Bonnabel, and in particular, the Invariant EKF (InEKF), we show that the error dynamics of the point contact-inertial system follows a log-linear autonomous differential equation; hence, the observable state variables can be rendered convergent with a domain of attraction that is independent of the system's trajectory.
Robotics
Contact-Aided Invariant Extended Kalman Filtering for Robot State Estimation
This filter combines contact-inertial dynamics with forward kinematic corrections to estimate pose and velocity along with all current contact points.
Robotics
LiDARTag: A Real-Time Fiducial Tag System for Point Clouds
Because of the LiDAR sensors' nature, rapidly changing ambient lighting will not affect the detection of a LiDARTag; hence, the proposed fiducial marker can operate in a completely dark environment.
Improvements to Target-Based 3D LiDAR to Camera Calibration
The homogeneous transformation between a LiDAR and monocular camera is required for sensor fusion tasks, such as SLAM.
Bayesian Spatial Kernel Smoothing for ScalableDense Semantic Mapping
This paper develops a Bayesian continuous 3D semantic occupancy map from noisy point cloud measurements.
Robotics
A New Framework for Registration of Semantic Point Clouds from Stereo and RGB-D Cameras
This paper reports on a novel nonparametric rigid point cloud registration framework that jointly integrates geometric and semantic measurements such as color or semantic labels into the alignment process and does not require explicit data association.
Continuous Direct Sparse Visual Odometry from RGB-D Images
This paper reports on a novel formulation and evaluation of visual odometry from RGB-D images.
Adaptive Continuous Visual Odometry from RGB-D Images
In this paper, we extend the recently developed continuous visual odometry framework for RGB-D cameras to an adaptive framework via online hyperparameter learning.
Global Unifying Intrinsic Calibration for Spinning and Solid-State LiDARs
By modeling the calibration parameters as an element of a special matrix Lie Group, we achieve a unifying view of calibration for different types of LiDARs.
Rapid Trajectory Optimization Using C-FROST with Illustration on a Cassie-Series Dynamic Walking Biped
One of the big attractions of low-dimensional models for gait design has been the ability to compute solutions rapidly, whereas one of their drawbacks has been the difficulty in mapping the solutions back to the target robot.
Robotics Systems and Control
Optimal Target Shape for LiDAR Pose Estimation
However, symmetric shapes lead to pose ambiguity when using sparse sensor data such as LiDAR point clouds and suffer from the quantization uncertainty of the LiDAR.
Hybrid Contact Preintegration for Visual-Inertial-Contact State Estimation Using Factor Graphs
The factor graph framework is a convenient modeling technique for robotic state estimation where states are represented as nodes, and measurements are modeled as factors.
Robotics
Legged Robot State-Estimation Through Combined Forward Kinematic and Preintegrated Contact Factors
We introduce forward kinematic factors and preintegrated contact factors into a factor graph framework that can be incrementally solved in real-time.
Robotics
