deepsense.ai's Research on Robotics to be Presented at Prestigious 1st Annual Conference on Robot Learning

deepsense.ai's paper has been recognized by the General Chairs of the Conference on Robot Learning (CoRL) as one of 11 in the reinforcement learning and robotics category. It will be presented in November at Google's headquarters in San Francisco.

PALO ALTO, California, Sept. 14, 2017 /PRNewswire/ -- In a recent research project, members of deepsense.ai's machine learning team, Maciej Klimek, Henryk Michalewski and Piotr Miłoś, trained a robotic arm to grip a can of coke using reinforcement learning - in other words, through trial and error. The particular method the team developed was selected for presentation at the prestigious new robotics conference, CoRL 2017. The conference focuses on the intersection of robotics and machine learning and is being organized with the help of the International Foundation of Robotics Research (IFRR). deepsense.ai's 'Hierarchical Reinforcement Learning with Parameters' will be featured along with 10 other standout archival papers on reinforcement learning and robotics selected for presentation at the conference and publication after the event.


The novelty of the approach presented in the paper comes from a clever division between simpler micro-actions and general goals. The methods developed by deepsense.ai's team are not limited to robotic arms, but could be used, for example, to train humanoid robots to combine single steps into a walk or a run.

According to Henryk Michalewski, Senior Data Scientist at deepsense.ai and an assistant professor at the University of Warsaw, "In recent years reinforcement learning has brought a number of striking new ideas to practical computer science. First, the DeepMind team managed to create bots which achieved superhuman performance in arcade games. Then, using a more sophisticated training methodology, they created a bot which beat the top human player at Go. A few weeks ago Open AI showed a bot that defeated the best human players at DOTA 2. At deepsense.ai, we also research reinforcement learning used in robotics, and we're happy to have our work recognized on the international AI scene".

Watch short videos with the robotic arm actions simulated during research: https://goo.gl/xMCjdL


About deepsense.ai


deepsense.ai delivers AI solutions and supports organizations in unlocking their data potential at all stages. The company created Neptune, a Machine Learning Lab provided as a service for data scientists to speed up the development and productionization of machine learning models.

Featured Product

BitFlow Introduces 6th Generation Camera Link Frame Grabber: The Axion

BitFlow Introduces 6th Generation Camera Link Frame Grabber: The Axion

BitFlow has offered a Camera Link frame grabbers for almost 15 years. This latest offering, our 6th generation combines the power of CoaXPress with the requirements of Camera Link 2.0. Enabling a single or two camera system to operate at up to 850 MB/S per camera, the Axion-CL family is the best choice for CL frame grabber. Like the Cyton-CXP frame grabber, the Axion-CL leverages features such as the new StreamSync system, a highly optimized DMA engine, and expanded I/O capabilities that provide unprecedented flexibility in routing. There are two options available; Axion 1xE & Axion 2xE. The Axion 1xE is compatible with one base, medium, full or 80-bit camera offering PoCL, Power over Camera Link, on both connectors. The Axion 2xE is compatible with two base, medium, full or 80-bit cameras offering PoCL on both connectors for both cameras. The Axion-CL is a culmination of the continuous improvements and updates BitFlow has made to Camera Link frame grabbers.