1 code implementation • 1 Aug 2023 • Pia Hanfeld, Khaled Wahba, Marina M. -C. Höhne, Michael Bussmann, Wolfgang Hönig
We introduce flying adversarial patches, where multiple images are mounted on at least one other flying robot and therefore can be placed anywhere in the field of view of a victim multirotor.
1 code implementation • 22 May 2023 • Pia Hanfeld, Marina M. -C. Höhne, Michael Bussmann, Wolfgang Hönig
We introduce flying adversarial patches, where an image is mounted on another flying robot and therefore can be placed anywhere in the field of view of a victim multirotor.
no code implementations • 10 Dec 2020 • Guanya Shi, Wolfgang Hönig, Xichen Shi, Yisong Yue, Soon-Jo Chung
We present Neural-Swarm2, a learning-based method for motion planning and control that allows heterogeneous multirotors in a swarm to safely fly in close proximity.
no code implementations • 6 Mar 2020 • Guanya Shi, Wolfgang Hönig, Yisong Yue, Soon-Jo Chung
We design a stable nonlinear tracking controller using the learned model.
2 code implementations • 11 Mar 2019 • Artem Molchanov, Tao Chen, Wolfgang Hönig, James A. Preiss, Nora Ayanian, Gaurav S. Sukhatme
Quadrotor stabilizing controllers often require careful, model-specific tuning for safe operation.
Robotics
no code implementations • 15 Dec 2018 • Hang Ma, Wolfgang Hönig, T. K. Satish Kumar, Nora Ayanian, Sven Koenig
For example, we demonstrate that it can compute paths for hundreds of agents and thousands of tasks in seconds and is more efficient and effective than existing MAPD algorithms that use a post-processing step to adapt their paths to continuous agent movements with given velocities.
no code implementations • 30 Mar 2018 • Hang Ma, Wolfgang Hönig, Liron Cohen, Tansel Uras, Hong Xu, T. K. Satish Kumar, Nora Ayanian, Sven Koenig
In the plan-generation phase, the framework provides a computationally scalable method for generating plans that achieve high-level tasks for groups of robots and take some of their kinematic constraints into account.
no code implementations • 25 Apr 2017 • Wolfgang Hönig, T. K. Satish Kumar, Liron Cohen, Hang Ma, Sven Koenig, Nora Ayanian
Path planning for multiple robots is well studied in the AI and robotics communities.