Search Results for author: Caelan Reed Garrett

Found 13 papers, 6 papers with code

Sequence-Based Plan Feasibility Prediction for Efficient Task and Motion Planning

no code implementations3 Nov 2022 Zhutian Yang, Caelan Reed Garrett, Tomás Lozano-Pérez, Leslie Kaelbling, Dieter Fox

The core of our algorithm is PIGINet, a novel Transformer-based learning method that takes in a task plan, the goal, and the initial state, and predicts the probability of finding motion trajectories associated with the task plan.

Motion Planning Task and Motion Planning +1

Long-Horizon Manipulation of Unknown Objects via Task and Motion Planning with Estimated Affordances

no code implementations9 Aug 2021 Aidan Curtis, Xiaolin Fang, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Caelan Reed Garrett

We present a strategy for designing and building very general robot manipulation systems involving the integration of a general-purpose task-and-motion planner with engineered and learned perception modules that estimate properties and affordances of unknown objects.

Grasp Generation Motion Planning +2

Integrated Task and Motion Planning

no code implementations2 Oct 2020 Caelan Reed Garrett, Rohan Chitnis, Rachel Holladay, Beomjoon Kim, Tom Silver, Leslie Pack Kaelbling, Tomás Lozano-Pérez

The problem of planning for a robot that operates in environments containing a large number of objects, taking actions to move itself through the world as well as to change the state of the objects, is known as task and motion planning (TAMP).

Motion Planning Task and Motion Planning

Online Replanning in Belief Space for Partially Observable Task and Motion Problems

1 code implementation11 Nov 2019 Caelan Reed Garrett, Chris Paxton, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Dieter Fox

To solve multi-step manipulation tasks in the real world, an autonomous robot must take actions to observe its environment and react to unexpected observations.

Continuous Control

Automated motion planning for robotic assembly of discrete architectural structures

2 code implementations1 Oct 2018 Yijiang Huang, Caelan Reed Garrett, Caitlin Tobin Mueller

While robotics for architectural-scale construction has made significant progress in recent years, a major challenge remains in automatically planning robotic motion for the assembly of complex structures.


Active model learning and diverse action sampling for task and motion planning

2 code implementations2 Mar 2018 Zi Wang, Caelan Reed Garrett, Leslie Pack Kaelbling, Tomás Lozano-Pérez

Solving long-horizon problems in complex domains requires flexible generative planning that can combine primitive abilities in novel combinations to solve problems as they arise in the world.

Active Learning Motion Planning +1

PDDLStream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planning

4 code implementations23 Feb 2018 Caelan Reed Garrett, Tomás Lozano-Pérez, Leslie Pack Kaelbling

We extend PDDL to support a generic, declarative specification for these procedures that treats their implementation as black boxes.

Motion Planning

STRIPS Planning in Infinite Domains

4 code implementations1 Jan 2017 Caelan Reed Garrett, Tomás Lozano-Pérez, Leslie Pack Kaelbling

We introduce STRIPStream: an extension of the STRIPS language which can model these domains by supporting the specification of blackbox generators to handle complex constraints.

Motion Planning Task and Motion Planning

Backward-Forward Search for Manipulation Planning

no code implementations12 Apr 2016 Caelan Reed Garrett, Tomas Lozano-Perez, Leslie Pack Kaelbling

In this paper we address planning problems in high-dimensional hybrid configuration spaces, with a particular focus on manipulation planning problems involving many objects.

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