5 papers
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…
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…
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…
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…