no code implementations • 22 Jun 2023 • Xiaolin Fang, Caelan Reed Garrett, Clemens Eppner, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Dieter Fox
Task and Motion Planning (TAMP) approaches are effective at planning long-horizon autonomous robot manipulation.
no code implementations • 3 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.
no code implementations • 9 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.
no code implementations • 2 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).
1 code implementation • 8 Jun 2020 • Zi Wang, Caelan Reed Garrett, Leslie Pack Kaelbling, Tomás Lozano-Pérez
We use, and develop novel improvements on, state-of-the-art methods for active learning and sampling.
no code implementations • 6 Feb 2020 • Caelan Reed Garrett, Yijiang Huang, Tomás Lozano-Pérez, Caitlin Tobin Mueller
There is increasing demand for automated systems that can fabricate 3D structures.
1 code implementation • 11 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.
2 code implementations • 1 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.
Robotics
2 code implementations • 2 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.
4 code implementations • 23 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.
4 code implementations • 1 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.
no code implementations • 3 Aug 2016 • Caelan Reed Garrett, Leslie Pack Kaelbling, Tomas Lozano-Perez
We investigate learning heuristics for domain-specific planning.
no code implementations • 12 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.