3 papers
cs.RO2025
Efficient Collision Detection for Long and Slender Robotic Links in Euclidean Distance Fields: Application to a Forestry Crane
Marc-Philip Ecker, Bernhard Bischof, Minh Nhat Vu +3
Collision-free motion planning in complex outdoor environments relies heavily on perceiving the surroundings through exteroceptive sensors. A widely used approach represents the en…
cs.RO2025
Near Time-Optimal Hybrid Motion Planning for Timber Cranes
Marc-Philip Ecker, Bernhard Bischof, Minh Nhat Vu +3
Efficient, collision-free motion planning is essential for automating large-scale manipulators like timber cranes. They come with unique challenges such as hydraulic actuation cons…
cs.RO2025
GPU-Accelerated Motion Planning of an Underactuated Forestry Crane in Cluttered Environments
Minh Nhat Vu, Gerald Ebmer, Alexander Watcher +3
Autonomous large-scale machine operations require fast, efficient, and collision-free motion planning while addressing unique challenges such as hydraulic actuation limits and unde…