23 citations · 32 across the 4 of their papers we have counts for
5 papers
Learning to Imagine Manipulation Goals for Robot Task Planning
Chris Paxton, Kapil Katyal, Christian Rupprecht +2
Prospection is an important part of how humans come up with new task plans, but has not been explored in depth in robotics. Predicting multiple task-level is a challenging problem…
Temporal and Physical Reasoning for Perception-Based Robotic Manipulation
Felix Jonathan, Chris Paxton, Gregory D. Hager
Accurate knowledge of object poses is crucial to successful robotic manipulation tasks, and yet most current approaches only work in laboratory settings. Noisy sensors and cluttere…
User Experience of the CoSTAR System for Instruction of Collaborative Robots
Chris Paxton, Felix Jonathan, Andrew Hundt +2
How can we enable novice users to create effective task plans for collaborative robots? Must there be a tradeoff between generalizability and ease of use? To answer these questions…
Combining Neural Networks and Tree Search for Task and Motion Planning in Challenging Environments
Chris Paxton, Vasumathi Raman, Gregory D. Hager +1
We consider task and motion planning in complex dynamic environments for problems expressed in terms of a set of Linear Temporal Logic (LTL) constraints, and a reward function. We…
Towards Robot Task Planning From Probabilistic Models of Human Skills
Chris Paxton, Marin Kobilarov, Gregory D. Hager
We describe an algorithm for motion planning based on expert demonstrations of a skill. In order to teach robots to perform complex object manipulation tasks that can generalize ro…