Search Results for author: Anthony Francis

Found 9 papers, 1 papers with code

Gesture2Path: Imitation Learning for Gesture-aware Navigation

no code implementations19 Sep 2022 Catie Cuan, Edward Lee, Emre Fisher, Anthony Francis, Leila Takayama, Tingnan Zhang, Alexander Toshev, Sören Pirk

Our experiments indicate that our method is able to successfully interpret complex human gestures and to use them as a signal to generate socially compliant trajectories for navigation tasks.

Imitation Learning Model Predictive Control +2

Style-based quantum generative adversarial networks for Monte Carlo events

1 code implementation13 Oct 2021 Carlos Bravo-Prieto, Julien Baglio, Marco Cè, Anthony Francis, Dorota M. Grabowska, Stefano Carrazza

We propose and assess an alternative quantum generator architecture in the context of generative adversarial learning for Monte Carlo event generation, used to simulate particle physics processes at the Large Hadron Collider (LHC).

Data Augmentation

Evolving Rewards to Automate Reinforcement Learning

no code implementations18 May 2019 Aleksandra Faust, Anthony Francis, Dar Mehta

Many continuous control tasks have easily formulated objectives, yet using them directly as a reward in reinforcement learning (RL) leads to suboptimal policies.

Continuous Control Hyperparameter Optimization +2

Long-Range Indoor Navigation with PRM-RL

no code implementations25 Feb 2019 Anthony Francis, Aleksandra Faust, Hao-Tien Lewis Chiang, Jasmine Hsu, J. Chase Kew, Marek Fiser, Tsang-Wei Edward Lee

Long-range indoor navigation requires guiding robots with noisy sensors and controls through cluttered environments along paths that span a variety of buildings.

Navigate reinforcement-learning +2

Learning Navigation Behaviors End-to-End with AutoRL

no code implementations26 Sep 2018 Hao-Tien Lewis Chiang, Aleksandra Faust, Marek Fiser, Anthony Francis

The policies are trained in small, static environments with AutoRL, an evolutionary automation layer around Reinforcement Learning (RL) that searches for a deep RL reward and neural network architecture with large-scale hyper-parameter optimization.

Motion Planning reinforcement-learning +1

PRM-RL: Long-range Robotic Navigation Tasks by Combining Reinforcement Learning and Sampling-based Planning

no code implementations11 Oct 2017 Aleksandra Faust, Oscar Ramirez, Marek Fiser, Kenneth Oslund, Anthony Francis, James Davidson, Lydia Tapia

The RL agents learn short-range, point-to-point navigation policies that capture robot dynamics and task constraints without knowledge of the large-scale topology.

Reinforcement Learning (RL)

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