1 citations · 2 across the 12 of their papers we have counts for
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HiMemFormer: Hierarchical Memory-Aware Transformer for Multi-Agent Action Anticipation
Zirui Wang, Xinran Zhao, Simon Stepputtis +4
Understanding and predicting human actions has been a long-standing challenge and is a crucial measure of perception in robotics AI. While significant progress has been made in ant…
DyPNIPP: Predicting Environment Dynamics for RL-based Robust Informative Path Planning
Srujan Deolasee, Siva Kailas, Wenhao Luo +2
Informative path planning (IPP) is an important planning paradigm for various real-world robotic applications such as environment monitoring. IPP involves planning a path that can…
OffRIPP: Offline RL-based Informative Path Planning
Srikar Babu Gadipudi, Srujan Deolasee, Siva Kailas +3
Informative path planning (IPP) is a crucial task in robotics, where agents must design paths to gather valuable information about a target environment while adhering to resource c…
Escaping Local Minima: Hybrid Artificial Potential Field with Wall-Follower for Decentralized Multi-Robot Navigation
Joonkyung Kim, Sangjin Park, Wonjong Lee +3
We tackle the challenges of decentralized multi-robot navigation in environments with nonconvex obstacles, where complete environmental knowledge is unavailable. While reactive met…
ShapeGrasp: Zero-Shot Task-Oriented Grasping with Large Language Models through Geometric Decomposition
Samuel Li, Sarthak Bhagat, Joseph Campbell +4
Task-oriented grasping of unfamiliar objects is a necessary skill for robots in dynamic in-home environments. Inspired by the human capability to grasp such objects through intuiti…