1 citations · 2 across the 4 of their papers we have counts for
5 papers
Open-Set Ego-Noise Separation for Legged-Robot Audition via Annotation-Free Adaptation and Pretrained-Model Transfer
Koki Shoda, Jun Younes Louhi Kasahara, Aoba Koyanagi +2
This paper proposes an open-set ego-noise separation framework for legged-robot audition via annotation-free adaptation and pretrained-model transfer. The framework removes robot-s…
Moving Object Detection from Moving Camera Using Focus of Expansion Likelihood and Segmentation
Masahiro Ogawa, Qi An, Atsushi Yamashita
Separating moving and static objects from a moving camera viewpoint is essential for 3D reconstruction, autonomous navigation, and scene understanding in robotics. Existing approac…
Quantifying Memory Utilization with Effective State-Size
Rom N. Parnichkun, Neehal Tumma, Armin W. Thomas +6
The need to develop a general framework for architecture analysis is becoming increasingly important, given the expanding design space of sequence models. To this end, we draw insi…
DART-LLM: Dependency-Aware Multi-Robot Task Decomposition and Execution using Large Language Models
Yongdong Wang, Runze Xiao, Jun Younes Louhi Kasahara +4
Large Language Models (LLMs) have demonstrated promising reasoning capabilities in robotics; however, their application in multi-robot systems remains limited, particularly in hand…
State-Free Inference of State-Space Models: The Transfer Function Approach
Rom N. Parnichkun, Stefano Massaroli, Alessandro Moro +10
We approach designing a state-space model for deep learning applications through its dual representation, the transfer function, and uncover a highly efficient sequence parallel in…