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Found 11 papers, 1 papers with code
Fast Traversability Estimation for Wild Visual Navigation
We demonstrate the advantages of our approach with experiments and ablation studies in challenging environments in forests, parks, and grasslands.
Multi-modal curb detection and filtering
We propose a robust curb detection and filtering technique based on the fusion of camera semantics and dense lidar point clouds.
Multi-Camera LiDAR Inertial Extension to the Newer College Dataset
We present a multi-camera LiDAR inertial dataset of 4. 5 km walking distance as an expansion of the Newer College Dataset.
Balancing the Budget: Feature Selection and Tracking for Multi-Camera Visual-Inertial Odometry
We present a multi-camera visual-inertial odometry system based on factor graph optimization which estimates motion by using all cameras simultaneously while retaining a fixed overall feature budget.
Online Estimation of Diameter at Breast Height (DBH) of Forest Trees Using a Handheld LiDAR
While mobile LiDAR sensors are increasingly used to scan in ecology and forestry applications, reconstruction and characterisation are typically carried out offline (to the best of our knowledge).
VILENS: Visual, Inertial, Lidar, and Leg Odometry for All-Terrain Legged Robots
This bias is observable because of the tight fusion of this preintegrated velocity factor with vision, lidar, and IMU factors.
RLOC: Terrain-Aware Legged Locomotion using Reinforcement Learning and Optimal Control
We evaluate the robustness of our method over a wide variety of complex terrains.
Unified Multi-Modal Landmark Tracking for Tightly Coupled Lidar-Visual-Inertial Odometry
True integration of lidar features with standard visual features and IMU is made possible using a subtle passive synchronization of lidar and camera frames.
Online LiDAR-SLAM for Legged Robots with Robust Registration and Deep-Learned Loop Closure
The efficiency of our method comes from carefully designing the network architecture to minimize the number of parameters such that this deep learning method can be deployed in real-time using only the CPU of a legged robot, a major contribution of this work.
SKD: Keypoint Detection for Point Clouds using Saliency Estimation
We present SKD, a novel keypoint detector that uses saliency to determine the best candidates from a point cloud for tasks such as registration and reconstruction.
Learning to See the Wood for the Trees: Deep Laser Localization in Urban and Natural Environments on a CPU
Localization in challenging, natural environments such as forests or woodlands is an important capability for many applications from guiding a robot navigating along a forest trail to monitoring vegetation growth with handheld sensors.
