collaborators

7 papers

cs.RO2026

Task-Space Constrained Stochastic Trajectory Optimization for Time-Optimal Forestry Crane Motion Planning

Marc-Philip Ecker, Christoph Fröhlich, Bernhard Bischof +2

Efficient, collision-free, and time-optimal motion planning is a fundamental requirement for autonomous forestry cranes operating under hydraulic pump-flow constraints. The Via-Poi…

cs.CV2026

Conformal Cross-Modal Active Learning

Huy Hoang Nguyen, Cédric Jung, Shirin Salehi +3

Foundation models for vision have transformed visual recognition with powerful pretrained representations and strong zero-shot capabilities, yet their potential for data-efficient…

cs.AI2026

Agentic LLM Planning via Step-Wise PDDL Simulation: An Empirical Characterisation

Kai Göbel, Pierrick Lorang, Patrik Zips +1

Task planning, the problem of sequencing actions to reach a goal from an initial state, is a core capability requirement for autonomous robotic systems. Whether large language mode…

cs.RO2026

Autonomous Block Assembly for Boom Cranes with Passive Joint Dynamics: Integrated Vision MPC Control

Gerald Ebmer, Minh Nhat Vu, Tobias Glück +1

This paper presents an autonomous control framework for articulated boom cranes performing prefabricated block assembly in construction environments. The key challenge addressed is…

cs.RO2026

A Collision-Free Sway Damping Model Predictive Controller for Safe and Reactive Forestry Crane Navigation

Marc-Philip Ecker, Christoph Fröhlich, Johannes Huemer +4

Forestry cranes operate in dynamic, unstructured outdoor environments where simultaneous collision avoidance and payload sway control are critical for safe navigation. Existing app…

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…