2 papers
cs.RO2026
Large-Language-Model-Guided State Estimation for Partially Observable Task and Motion Planning
Yoonwoo Kim, Raghav Arora, Roberto MartÃn-MartÃn +3
Robot planning in partially observable environments, where not all objects are known or visible, is a challenging problem, as it requires reasoning under uncertainty through partia…
cs.RO2025
Anticipate & Act : Integrating LLMs and Classical Planning for Efficient Task Execution in Household Environments
Raghav Arora, Shivam Singh, Karthik Swaminathan +6
Assistive agents performing household tasks such as making the bed or cooking breakfast often compute and execute actions that accomplish one task at a time. However, efficiency ca…