12 citations · 16 across the 8 of their papers we have counts for
8 papers
Few-Shot Demonstration-Driven Task Coordination and Trajectory Execution for Multi-Robot Systems
Taehyeon Kim, Vishnunandan L. N. Venkatesh, Byung-Cheol Min
Learning coordinated behaviors for multi-robot systems from only a few demonstrations is difficult because temporal task dependencies and spatial trajectory generation are tightly…
ZeroSCD: Zero-Shot Street Scene Change Detection
Shyam Sundar Kannan, Byung-Cheol Min
Scene Change Detection is a challenging task in computer vision and robotics that aims to identify differences between two images of the same scene captured at different times. Tra…
Learning from Demonstration Framework for Multi-Robot Systems Using Interaction Keypoints and Soft Actor-Critic Methods
Vishnunandan L. N. Venkatesh, Byung-Cheol Min
Learning from Demonstration (LfD) is a promising approach to enable Multi-Robot Systems (MRS) to acquire complex skills and behaviors. However, the intricate interactions and coord…
ZeroCAP: Zero-Shot Multi-Robot Context Aware Pattern Formation via Large Language Models
Vishnunandan L. N. Venkatesh, Byung-Cheol Min
Incorporating language comprehension into robotic operations unlocks significant advancements in robotics, but also presents distinct challenges, particularly in executing spatiall…
PlaceFormer: Transformer-based Visual Place Recognition using Multi-Scale Patch Selection and Fusion
Shyam Sundar Kannan, Byung-Cheol Min
Visual place recognition is a challenging task in the field of computer vision, and autonomous robotics and vehicles, which aims to identify a location or a place from visual input…
DynaCon: Dynamic Robot Planner with Contextual Awareness via LLMs
Gyeongmin Kim, Taehyeon Kim, Shyam Sundar Kannan +3
Mobile robots often rely on pre-existing maps for effective path planning and navigation. However, when these maps are unavailable, particularly in unfamiliar environments, a diffe…
SMART-LLM: Smart Multi-Agent Robot Task Planning using Large Language Models
Shyam Sundar Kannan, Vishnunandan L. N. Venkatesh, Byung-Cheol Min
In this work, we introduce SMART-LLM, an innovative framework designed for embodied multi-robot task planning. SMART-LLM: Smart Multi-Agent Robot Task Planning using Large Language…
T-RECS: Training for Rate-Invariant Embeddings by Controlling Speed for Action Recognition
Madan Ravi Ganesh, Eric Hofesmann, Byungsu Min +2
An action should remain identifiable when modifying its speed: consider the contrast between an expert chef and a novice chef each chopping an onion. Here, we expect the novice che…