Reaching Through Latent Space: From Joint Statistics to Path Planning in Manipulation

Author:

Hung Chia-Man1ORCID,Zhong Shaohong2,Goodwin Walter1,Jones Oiwi Parker2,Engelcke Martin2,Havoutis Ioannis3ORCID,Posner Ingmar2

Affiliation:

1. Applied AI Lab (A2I), U.K.

2. Applied AI Lab (A2I), Oxford Robotics Institute (ORI), University of Oxford, Oxford, U.K.

3. Dynamic Robot Systems (DRS), Oxford Robotics Institute (ORI), University of Oxford, Oxford, U.K.

Funder

UKRI/EPSRC Programme

NIA

RAIN

Offshore Robotics for Certification of Assets

Clarendon Fund

Amazon Web Services

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Reference45 articles.

1. RRT-connect: An efficient approach to single-query path planning

2. A depth space approach to human-robot collision avoidance

3. beta-VAE: Learning basic visual concepts with a constrained variational framework;higgins;Proc Int Conf Learn Representations,0

4. Stochastic backpropagation and approximate inference in deep generative models;rezende;Proc Int Conf Mach Learn,0

5. Auto-encoding variational bayes;kingma;Proc Int Conf Learn Representations,0

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