12 citations · 17 across the 5 of their papers we have counts for
6 papers
HydroMap: Probabilistic Water Surface Elevation Mapping for Semantic Scene Representation in Inland Waterways
Zhongbi Luo, Yunjia Wang, Herman Bruyninckx +1
Autonomous surface vehicles operating in inland waterways require a persistent representation of both surrounding structures and the water surface. LiDAR-based simultaneous localiz…
Efficient Constrained Dynamics Algorithms based on an Equivalent LQR Formulation using Gauss' Principle of Least Constraint
Ajay Suresha Sathya, Herman Bruyninckx, Wilm Decre +1
We derive a family of efficient constrained dynamics algorithms by formulating an equivalent linear quadratic regulator (LQR) problem using Gauss principle of least constraint and…
Autonomous Ground Navigation in Highly Constrained Spaces: Lessons learned from The 2nd BARN Challenge at ICRA 2023
Xuesu Xiao, Zifan Xu, Garrett Warnell +8
The 2nd BARN (Benchmark Autonomous Robot Navigation) Challenge took place at the 2023 IEEE International Conference on Robotics and Automation (ICRA 2023) in London, UK and continu…
Energy-Efficient Control of Cable Robots Exploiting Natural Dynamics and Task Knowledge
Boris Deroo, Erwin Aertbeliën, Wilm Decré +1
This paper focusses on the energy-efficient control of a cable-driven robot for tasks that only require precise positioning at few points in their motion, and where that accuracy c…
Towards a Domain Specific Language for a Scene Graph based Robotic World Model
Sebastian Blumenthal, Herman Bruyninckx
Robot world model representations are a vital part of robotic applications. However, there is no support for such representations in model-driven engineering tool chains. This work…
A Rigorously Bayesian Beam Model and an Adaptive Full Scan Model for Range Finders in Dynamic Environments
Tinne De Laet, Joris De Schutter, Herman Bruyninckx
This paper proposes and experimentally validates a Bayesian network model of a range finder adapted to dynamic environments. All modeling assumptions are rigorously explained, and…