Survey on AI‐Enabled Computer Vision Technologies and Applications for Space Robotic Missions
ABSTRACT This survey provides a comprehensive overview of recent advancements and challenges in Artificial Intelligence (AI)‐enabled computer vision (CV) techniques for space robotic missions, spanning critical phases such as Entry, Descent, and Landing (EDL), orbital operations, and planetary surface exploration.
Maciej Quoos +6 more
wiley +1 more source
Integrating Line Transect Distance Sampling and Spatial Analysis to Assess Local Density and Habitat Use of <i>Capra aegagrus</i> in Batman Province, Türkiye. [PDF]
Yıldırım E, Ulutürk S.
europepmc +1 more source
ABSTRACT Planetary exploration is rapidly gaining importance within the space research community. Autonomous locomotion of rovers requires consideration of several mobility aspects to ensure safety, including avoiding hazardous areas that can cause the robot to become immobilized in soft soil or damaged in sharp terrains.
Alessio De Luca +3 more
wiley +1 more source
Downscaling the spatial resolution of satellite imagery based on morphometric parameters to estimate the Topographic Wetness Index using GIS tools. [PDF]
Shabbir H +6 more
europepmc +1 more source
Automated Classification of Basic-Level Terrain Features in Digital Elevation Models
Linda H. Graff
openalex +2 more sources
Control System for the Navigation of the Agricultural Robots: A Review
ABSTRACT Control systems for the navigation of autonomous agricultural robots—particularly those operating in uneven terrain and in the presence of static or dynamic obstacles—have advanced considerably in recent years. As conventional machinery evolves toward increasingly automated systems, the design of reliable navigation controllers has become ...
Edna Carolina Moriones Polanía +3 more
wiley +1 more source
Delineation of palaeochannels using DEM and spectral indices in the Gundar basin of Kadaladi region. [PDF]
Narayanan MSS +5 more
europepmc +1 more source
Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning
ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi +3 more
wiley +1 more source

