An Open-Source System for Vision-Based Micro-Aerial Vehicle Mapping, Planning, and Flight in Cluttered Environments

Abstract

We present an open-source system for Micro-Aerial Vehicle autonomous navigation from vision-based sensing. Our system focuses on dense mapping, safe local planning, and global trajectory generation, especially when using narrow field of view sensors in very cluttered environments. In addition, details about other necessary parts of the system and special considerations for applications in real-world scenarios are presented. We focus our experiments on evaluating global planning, path smoothing, and local planning methods on real maps made on MAVs in realistic search and rescue and industrial inspection scenarios. We also perform thousands of simulations in cluttered synthetic environments, and finally validate the complete system in real-world experiments.

References in corpus (10)

• ORB-SLAM: a Versatile and Accurate Monocular SLAM System
• VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator
• Informed RRT*: Optimal Sampling-based Path Planning Focused via Direct Sampling of an Admissible Ellipsoidal Heuristic
• Voxblox: Incremental 3D Euclidean Signed Distance Fields for On-Board MAV Planning
• maplab: An Open Framework for Research in Visual-inertial Mapping and Localization
• Real-Time Trajectory Replanning for MAVs using Uniform B-splines and a 3D Circular Buffer
• Fast, Autonomous Flight in GPS-Denied and Cluttered Environments
• Safe Local Exploration for Replanning in Cluttered Unknown Environments for Micro-Aerial Vehicles
• High-speed Flight in an Ergodic Forest
• Nonlinear Model Predictive Control for Multi-Micro Aerial Vehicle Robust Collision Avoidance

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• Good Graph to Optimize: Cost-Effective, Budget-Aware Bundle Adjustment in Visual SLAM
• Generating Large-Scale Trajectories Efficiently using Double Descriptions of Polynomials
• Teach-Repeat-Replan: A Complete and Robust System for Aggressive Flight in Complex Environments
• Mapless-Planner: A Robust and Fast Planning Framework for Aggressive Autonomous Flight without Map Fusion
• A Small Form Factor Aerial Research Vehicle for Pick-and-Place Tasks with Onboard Real-Time Object Detection and Visual Odometry
• Depth-based Sampling and Steering Constraints for Memoryless Local Planners
• Closed-Loop Benchmarking of Stereo Visual-Inertial SLAM Systems: Understanding the Impact of Drift and Latency on Tracking Accuracy
• Advanced Algorithms of Collision Free Navigation and Flocking for Autonomous UAVs
• Scalable Outdoors Autonomous Drone Flight with Visual-Inertial SLAM and Dense Submaps Built without LiDAR
• A Hybrid PEM-GP Framework for Uncertainty-Aware System Identification of Quadcopters