100 citations · 587 across the 34 of their papers we have counts for
34 papers
Evolutionary Curriculum Training for DRL-Based Navigation Systems
Max Asselmeier, Zhaoyi Li, Kelin Yu +1
In recent years, Deep Reinforcement Learning (DRL) has emerged as a promising method for robot collision avoidance. However, such DRL models often come with limitations, such as ad…
Language-Guided Traffic Simulation via Scene-Level Diffusion
Ziyuan Zhong, Davis Rempe, Yuxiao Chen +5
Realistic and controllable traffic simulation is a core capability that is necessary to accelerate autonomous vehicle (AV) development. However, current approaches for controlling…
Partial-View Object View Synthesis via Filtered Inversion
Fan-Yun Sun, Jonathan Tremblay, Valts Blukis +11
We propose Filtering Inversion (FINV), a learning framework and optimization process that predicts a renderable 3D object representation from one or few partial views. FINV address…
Zero-Shot Object Searching Using Large-scale Object Relationship Prior
Hongyi Chen, Ruinian Xu, Shuo Cheng +2
Home-assistant robots have been a long-standing research topic, and one of the biggest challenges is searching for required objects in housing environments. Previous object-goal na…
MimicPlay: Long-Horizon Imitation Learning by Watching Human Play
Chen Wang, Linxi Fan, Jiankai Sun +5
Imitation learning from human demonstrations is a promising paradigm for teaching robots manipulation skills in the real world. However, learning complex long-horizon tasks often r…
Foundation Models for Semantic Novelty in Reinforcement Learning
Tarun Gupta, Peter Karkus, Tong Che +2
Effectively exploring the environment is a key challenge in reinforcement learning (RL). We address this challenge by defining a novel intrinsic reward based on a foundation model,…