4 citations · 17 across the 16 of their papers we have counts for
7 papers · 1 filter
Continuous-Time State Estimation Methods in Robotics: A Survey
William Talbot, Julian Nubert, Turcan Tuna +5
Accurate, efficient, and robust state estimation is more important than ever in robotics as the variety of platforms and complexity of tasks continue to grow. Historically, discret…
IPPON: Common Sense Guided Informative Path Planning for Object Goal Navigation
Kaixian Qu, Jie Tan, Tingnan Zhang +3
Navigating efficiently to an object in an unexplored environment is a critical skill for general-purpose intelligent robots. Recent approaches to this object goal navigation proble…
Reinforcement Learning Control for Autonomous Hydraulic Material Handling Machines with Underactuated Tools
Filippo A. Spinelli, Pascal Egli, Julian Nubert +6
The precise and safe control of heavy material handling machines presents numerous challenges due to the hard-to-model hydraulically actuated joints and the need for collision-free…
ETHcavation: A Dataset and Pipeline for Panoptic Scene Understanding and Object Tracking in Dynamic Construction Environments
Lorenzo Terenzi, Julian Nubert, Pol Eyschen +4
Construction sites are challenging environments for autonomous systems due to their unstructured nature and the presence of dynamic actors, such as workers and machinery. This work…
MultiViPerFrOG: A Globally Optimized Multi-Viewpoint Perception Framework for Camera Motion and Tissue Deformation
Guido Caccianiga, Julian Nubert, Cesar Cadena +2
Reconstructing the 3D shape of a deformable environment from the information captured by a moving depth camera is highly relevant to surgery. The underlying challenge is the fact t…
Informed, Constrained, Aligned: A Field Analysis on Degeneracy-aware Point Cloud Registration in the Wild
Turcan Tuna, Julian Nubert, Patrick Pfreundschuh +3
The ICP registration algorithm has been a preferred method for LiDAR-based robot localization for nearly a decade. However, even in modern SLAM solutions, ICP can degrade and becom…
ROS-LLM: A ROS framework for embodied AI with task feedback and structured reasoning
Christopher E. Mower, Yuhui Wan, Hongzhan Yu +20
We present a framework for intuitive robot programming by non-experts, leveraging natural language prompts and contextual information from the Robot Operating System (ROS). Our sys…