33 citations · 120 across the 10 of their papers we have counts for
13 papers · 1 filter
Technical Report: A Hierarchical Deliberative-Reactive System Architecture for Task and Motion Planning in Partially Known Environments
Vasileios Vasilopoulos, Sebastian Castro, William Vega-Brown +2
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 react…
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
Nicholas Roy, Ingmar Posner, Tim Barfoot +17
Machine learning has long since become a keystone technology, accelerating science and applications in a broad range of domains. Consequently, the notion of applying learning metho…
Active Learning of Abstract Plan Feasibility
Michael Noseworthy, Caris Moses, Isaiah Brand +4
Long horizon sequential manipulation tasks are effectively addressed hierarchically: at a high level of abstraction the planner searches over abstract action sequences, and when a…
Learning and Planning for Temporally Extended Tasks in Unknown Environments
Christopher Bradley, Adam Pacheck, Gregory J. Stein +3
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…
Reactive Task and Motion Planning under Temporal Logic Specifications
Shen Li, Daehyung Park, Yoonchang Sung +2
We present a task-and-motion planning (TAMP) algorithm robust against a human operator's cooperative or adversarial interventions. Interventions often invalidate the current plan a…
Visual Prediction of Priors for Articulated Object Interaction
Caris Moses, Michael Noseworthy, Leslie Pack Kaelbling +2
Exploration in novel settings can be challenging without prior experience in similar domains. However, humans are able to build on prior experience quickly and efficiently. Childre…