Safety constrained learning for industrial manipulators

1)
Ocado group builds the Ocado Smart Platform, an end-to-end ecommerce, fulfilment, and logistics solution for smart online grocery businesses. This team develops cutting edge technologies across robotics, artificial intelligence, machine learning, and data science to support various stages of warehouse automation and logistics. Each application requires robots with specific capabilities tailored to different tasks.
2)
Behaviour cloning, imitation learning and reinforcement learning are growing in popularity for learning behaviours that generalize across tasks, but deploying these methods on industrial robots presents unique safety challenges. This project aims to identify, discover and develop robust methods for training that ensure safe operation of industrial robots performing pick and place tasks.
3)
For Ocado, this means increased efficiency and safety in their warehouses. This in turn improves the speed, efficiency, and reliability of the grocery distribution industry. Ocado will provide the robots, simulation software, task definition, and guidance to support this project.

Faculty Supervisor:

Beno Benhabib

Student:

Partner:

Ocado Technology

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program: