no code implementations • 19 May 2022 • Yu-Wei Chao, Chris Paxton, Yu Xiang, Wei Yang, Balakumar Sundaralingam, Tao Chen, Adithyavairavan Murali, Maya Cakmak, Dieter Fox
We analyze the performance of a set of baselines and show a correlation with a real-world evaluation.
no code implementations • 31 Mar 2022 • Wei Yang, Balakumar Sundaralingam, Chris Paxton, Iretiayo Akinola, Yu-Wei Chao, Maya Cakmak, Dieter Fox
However, how to responsively generate smooth motions to take an object from a human is still an open question.
no code implementations • 9 Nov 2021 • Andreea Bobu, Chris Paxton, Wei Yang, Balakumar Sundaralingam, Yu-Wei Chao, Maya Cakmak, Dieter Fox
Second, we treat this low-dimensional concept as an automatic labeler to synthesize a large-scale high-dimensional data set with the simulator.
no code implementations • 17 Nov 2020 • Wei Yang, Chris Paxton, Arsalan Mousavian, Yu-Wei Chao, Maya Cakmak, Dieter Fox
We demonstrate the generalizability, usability, and robustness of our approach on a novel benchmark set of 26 diverse household objects, a user study with naive users (N=6) handing over a subset of 15 objects, and a systematic evaluation examining different ways of handing objects.
no code implementations • 12 Mar 2020 • Wei Yang, Chris Paxton, Maya Cakmak, Dieter Fox
In this paper, we propose an approach for human-to-robot handovers in which the robot meets the human halfway, by classifying the human's grasp of the object and quickly planning a trajectory accordingly to take the object from the human's hand according to their intent.
2 code implementations • 10 Jul 2019 • Jesse Thomason, Michael Murray, Maya Cakmak, Luke Zettlemoyer
To train agents that search an environment for a goal location, we define the Navigation from Dialog History task.
1 code implementation • 2 Jul 2019 • Nick Walker, Yu-Tang Peng, Maya Cakmak
To address this challenge, we propose an approach that leverages neural semantic parsing methods in combination with contextual word embeddings to enable the training of a semantic parser with little data and without domain specific parser engineering.