Reactive Navigation on Natural Environments by Continuous Classification of Ground Traversability
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Summary
A case study of mobile robot Andabata that classifies traversable points from 3D laser scans acquired in motion of its vicinity to build 2D local traversability maps is described.
- Type
- letter
- Published
- 2020-11-01
- Cited by
- 22
- References
- 43
- Access
- Open access
- OpenAlex
- https://openalex.org/W3102033119
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:226845996
Keywords
Robot, Computer science, Artificial intelligence, Terrain, Key (lock)
References
- Probabilistic Terrain Analysis For High-Speed Desert Driving
- Off-Road Terrain Traversability Analysis and Hazard Avoidance for UGVs
- Traversability analysis for mobile robots in outdoor environments: A semi-supervised learning approach based on 3D-lidar data
- Terrain traversability analysis methods for unmanned ground vehicles: A survey
- Reinforcement learning in robotics: A survey
- Stereo-vision-based perception capabilities developed during the Robotics Collaborative Technology Alliances program
- Autonomous over-the-horizon navigation using LIDAR data
- Navigability analysis of natural terrains with fuzzy elevation maps from ground-based 3D range scans
- Improving Point Cloud Accuracy Obtained from a Moving Platform for Consistent Pile Attack Pose Estimation
- Autonomous ground vehicle navigation method in complex environment
- 3D traversability awareness for rough terrain mobile robots
- Collapsible cubes: Removing overhangs from 3D point clouds to build local navigable elevation maps
- V-REP: A versatile and scalable robot simulation framework
- Global and regional path planners for integrated planning and navigation
- 3D obstacle detection and avoidance in vegetated off-road terrain
- T-transformation: traversability analysis for navigation on rugged terrain
- Construction and calibration of a low-cost 3D laser scanner with 360° field of view for mobile robots
- Autonomous Rover Navigation on Unknown Terrains: Functions and Integration
- Tradeoffs Between Directed and Autonomous Driving on the Mars Exploration Rovers
- Terrain Classification in Complex Three‐dimensional Outdoor Environments
Cited by
- A Dynamic Motion Analysis of a Six-Wheel Ground Vehicle for Emergency Intervention Actions
- Means of IoT and Fuzzy Cognitive Maps in Reactive Navigation of Ubiquitous Robots
- Aspects Regarding of a UGV Fire Fighting Thermal Shield
- Hexagonal Grid-Based Framework for Mobile Robot Navigation
- Image-Based Scene Recognition for Robot Navigation Considering Traversable Plants and Its Manual Annotation-Free Training
- Automatically Annotated Dataset of a Ground Mobile Robot in Natural Environments via Gazebo Simulations
- Online Refinement of a Scene Recognition Model for Mobile Robots by Observing Human’s Interaction with Environments
- Reinforcement and Curriculum Learning for Off-Road Navigation of an UGV with a 3D LiDAR
- Exploración dinámica de fronteras en entornos desconocidos basada en la entropía
- Traversable Region Detection and Tracking for a Sparse 3D Laser Scanner for Off-Road Environments Using Range Images
- An Optimized Energy and Time Constraints-Based Path Planning for the Navigation of Mobile Robots Using an Intelligent Particle Swarm Optimization Technique
- A comprehensive survey of unmanned ground vehicle terrain traversability for unstructured environments and sensor technology insights
- Assessing Forest Traversability for Autonomous Mobile Systems Using Close-Range Airborne Laser Scanning
- Reachability Analysis of UAVs through Cluttered Environments
- Air-Ground Collaboration With SPOMP: Semantic Panoramic Online Mapping and Planning
- Autonomous Navigation of AGV by Tracking the Motion of UAV*
- Overview of Terrain Traversability Evaluation for Autonomous Robots
- ICR-based Kinematics for Wheeled Skid-Steer Vehicles on Firm Slopes*
- Autonomous Non-Communicative Navigation Assistance to the Ground Vehicle by an Aerial Vehicle
- Advances and Trends in Terrain Classification Methods for Off‐Road Perception
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