most citedMRNAV: Multi-Robot Aware Planning and Control Stack for Collision and Deadlock-free Navigation in Cluttered Environments

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2024

iDb-RRT: Sampling-based Kinodynamic Motion Planning with Motion Primitives and Trajectory Optimization

Joaquim Ortiz-Haro, Wolfgang Hönig, Valentin N. Hartmann +2

Rapidly-exploring Random Trees (RRT) and its variations have emerged as a robust and efficient tool for finding collision-free paths in robotic systems. However, adding dynamic con…

cs.RO20233 cited

MRNAV: Multi-Robot Aware Planning and Control Stack for Collision and Deadlock-free Navigation in Cluttered Environments

Baskın Şenbaşlar, Pilar Luiz, Wolfgang Hönig +1

Multi-robot collision-free and deadlock-free navigation in cluttered environments with static and dynamic obstacles is a fundamental problem for many applications. We introduce MRN…

cs.RO2023

Kidnapping Deep Learning-based Multirotors using Optimized Flying Adversarial Patches

Pia Hanfeld, Khaled Wahba, Marina M. -C. Höhne +2

Autonomous flying robots, such as multirotors, often rely on deep learning models that make predictions based on a camera image, e.g. for pose estimation. These models can predict…

cs.RO20232 cited

Comparison of Optimization-Based Methods for Energy-Optimal Quadrotor Motion Planning

Welf Rehberg, Joaquim Ortiz-Haro, Marc Toussaint +1

Quadrotors are agile flying robots that are challenging to control. Considering the full dynamics of quadrotors during motion planning is crucial to achieving good solution quality…

cs.RO2023

RLSS: Real-time, Decentralized, Cooperative, Networkless Multi-Robot Trajectory Planning using Linear Spatial Separations

Baskın Şenbaşlar, Wolfgang Hönig, Nora Ayanian

Trajectory planning for multiple robots in shared environments is a challenging problem especially when there is limited communication available or no central entity. In this artic…