1 code implementation • 27 Sep 2023 • Hanzhe Teng, Yipeng Wang, Xiaoao Song, Konstantinos Karydis
In this work we introduce the CitrusFarm dataset, a comprehensive multimodal sensory dataset collected by a wheeled mobile robot operating in agricultural fields.
1 code implementation • ICCV 2023 • Cody Simons, Dripta S. Raychaudhuri, Sk Miraj Ahmed, Suya You, Konstantinos Karydis, Amit K. Roy-Chowdhury
In this work, we relax both of these assumptions by addressing the problem of adapting a set of models trained independently on uni-modal data to a target domain consisting of unlabeled multi-modal data, without having access to the original source dataset.
1 code implementation • 4 Oct 2022 • Hanzhe Teng, Dimitrios Chatziparaschis, Xinyue Kan, Amit K. Roy-Chowdhury, Konstantinos Karydis
Results demonstrate that our proposed CED keypoint detector requires minimal computational time while attaining high repeatability.
no code implementations • 9 Aug 2022 • Amel Dechemi, Vikarn Bhakri, Ipsita Sahin, Arjun Modi, Julya Mestas, Pamodya Peiris, Dannya Enriquez Barrundia, Elena Kokkoni, Konstantinos Karydis
We evaluate the efficiency of our proposed approach and compare its performance against other learning-based network structures in terms of capability of capturing temporal inter-dependencies and accuracy of detection of reaching onset and offset.
no code implementations • 6 Dec 2017 • Kartik Mohta, Michael Watterson, Yash Mulgaonkar, Sikang Liu, Chao Qu, Anurag Makineni, Kelsey Saulnier, Ke Sun, Alex Zhu, Jeffrey Delmerico, Konstantinos Karydis, Nikolay Atanasov, Giuseppe Loianno, Davide Scaramuzza, Kostas Daniilidis, Camillo Jose Taylor, Vijay Kumar
One of the most challenging tasks for a flying robot is to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little to no a-priori knowledge of the operating environment.
Robotics
no code implementations • ICLR 2018 • Arbaaz Khan, Clark Zhang, Nikolay Atanasov, Konstantinos Karydis, Vijay Kumar, Daniel D. Lee
The third part uses a network controller that learns to store those specific instances of past information that are necessary for planning.
no code implementations • 23 May 2017 • Steven W. Chen, Nikolay Atanasov, Arbaaz Khan, Konstantinos Karydis, Daniel D. Lee, Vijay Kumar
This work is a first thorough study of memory structures for deep-neural-network-based robot navigation, and offers novel tools to train such networks from supervision and quantify their ability to generalize to unseen scenarios.