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Sebastian Castro

2 accepted papers

2022

A Hierarchical Deliberative-Reactive System Architecture for Task and Motion Planning in Partially Known Environments

ICRA 2022poster

We describe a task and motion planning architecture for highly dynamic systems that combines a domain-independent sampling-based deliberative planning algorithm with a global reactive planner. We leverage the recent development of a reactive, vector field planner that provides guarantees of reachabi…

Cited by 3SourceScholar
2021

Learning and Planning for Temporally Extended Tasks in Unknown Environments

ICRA 2021poster

We propose a novel planning technique for satisfying tasks specified in temporal logic in partially revealed environments. We define high-level actions derived from the environment and the given task itself, and estimate how each action contributes to progress towards completing the task. As the map…

Cited by 26SourceScholar