Kindred Introduces SenseActTM, the First Reinforcement Learning Open-Source Toolkit for Physical Robots

AI and robotics company launches benchmark task suite for developing and evaluating reinforcement learning methods on robotic hardware.

Kindred, an AI and robotics company that builds intelligence for robots, has announced today the launch of SenseAct, the first open-source toolkit to set-up reinforcement learning tasks on physical robots. Kindreds SenseAct was created to provide robotics developers and researchers with a consistent, learnable interface that efficiently controls for time delays, a factor that simulation environments arent hindered by.

"SenseAct is an important new step in machine learning research on robots, enabling consistent and reproducible results on physical robots for the first time. It will establish a standard that may greatly accelerate machine learning research on physical robots, pushing reinforcement learning to a new level of performance just as large standard data sets have for supervised learning," said Richard S. Sutton, professor of Computing Science and AITF Chair in Reinforcement Learning and Artificial Intelligence at University of Alberta.

SenseAct allows reinforcement learning agents written for OpenAIs popular "gym" simulator to learn behaviors for robots, by insulating them from the complexity of real-time control of robotic components. SenseActs guiding principles of minimizing delays and maximizing timing consistency via proactive computation lead to responsive learned behavior and reliable learning via state-of-the-art algorithms.

"This initial release focuses on tasks that explore timing, control frequency, action representation, partial observation, and sparse reward. We intend to update SenseAct as we define new tasks to reflect challenges in developing efficient, general, intuitive behaviors for our current and future products," says James Bergstra, Head of AI Research at Kindred.

SenseAct allows general reinforcement learning algorithms to learn diverse tasks on diverse robots, and is made freely available for anyone to explore and extend. For more information, visit

About Kindred

Founded in 2014, Kindred is building artificial intelligence for robotic grasping solutions. SORT, its first commercial product, is currently operating in major ecommerce retailers throughout the US. For more information, visit

Featured Product

ATI Industrial Automation at IMTS 2018

ATI Industrial Automation at IMTS 2018

ATI Industrial Automation's MC-10 Manual Tool Changer provides a cost-effective solution for quickly changing tools by hand. Its compact yet robust design is optimized for collaborative robot applications. The ergonomic twist-collar locking mechanism ensures a secure attachment of the tool and easy manual operation with tactile feedback. This Manual Tool Changer can carry payloads of up to 22 lbs and includes multiple fail-safe features that resist vibration and prevent loosening. The MC-10 Manual Tool Changer has integrated air pass-through connections and options to connect electrical utilities if needed. ATI will feature the new MC-10 along with a variety of other robotic demonstrations and product displays at this year's IMTS show in Chicago (Booth #236417).