5 papers
Policy Gradient with Self-Attention for Model-Free Distributed Nonlinear Multi-Agent Games
Eduardo Sebastián, Maitrayee Keskar, Eeman Iqbal +3
Multi-agent games in dynamic nonlinear settings are challenging due to the time-varying interactions among the agents and the non-stationarity of the (potential) Nash equilibria. I…
DexFuture: Hierarchical Future-State Visuomotor Targeting for Bimanual Dexterous Tool Use
Runfa Blark Li, Kuang-Ting Tu, Nikola Raicevic +6
Bimanual dexterous tool use remains challenging for robots due to high-dimensional hand configurations and complex hand-tool-object dynamics and contact. Most existing control poli…
Rainbow-DemoRL: Combining Improvements in Demonstration-Augmented Reinforcement Learning
Dwait Bhatt, Shih-Chieh Chou, Nikolay Atanasov
Several approaches have been proposed to improve the sample efficiency of online reinforcement learning (RL) by leveraging demonstrations collected offline. The offline data can be…
LTLCodeGen: Code Generation of Syntactically Correct Temporal Logic for Robot Task Planning
Behrad Rabiei, Mahesh Kumar A. R., Zhirui Dai +3
This paper focuses on planning robot navigation tasks from natural language specifications. We develop a modular approach, where a large language model (LLM) translates the natural…
LATMOS: Latent Automaton Task Model from Observation Sequences
Weixiao Zhan, Qiyue Dong, Eduardo Sebastián +1
Robot task planning from high-level instructions is an important step towards deploying fully autonomous robot systems in the service sector. Three key aspects of robot task planni…