In most traditional applications of industrial robots, humans program robots to carry out tasks. It takes a considerable amount of effort to program a robot to perform a new task. Robots cannot automatically adapt their actions in response to changes in the task. These challenges limit the number and types of applications where robots can be employed. Many emerging robotics applications require the use of multiple collaborating robots to operate under human supervision.
To be useful in such applications, robots will need to act as smart assistants by (1) programming themselves, (2) efficiently learning from the observed performance, (3) safely operating in the presence of uncertainty, (4) appropriately calling for help during the execution of challenging tasks, and (5) effectively communicating with humans.
This presentation will provide an overview of the advances in artificial intelligence that are being used to enable robots to make decisions. First, we will present an approach for automatically generating trajectories to enable robots to program themselves from task descriptions. Second, we will describe self-directed learning methods to equip robots with the ability to learn from observing the performance of previously-executed tasks and adapting their plans. Third, we will describe methods for robots to operate safely in the presence of uncertainty by generating contingency-aware plans. Fourth, we will discuss computational methods for endowing robots with introspective capabilities so that they can seek help from humans. Finally, we will present augmented reality-based interfaces for enabling robots to explain their decisions and elicit human guidance.
- Understand recent trends in industrial robots and their implications on manufacturing
- Select methods for generating trajectories for industrial robots in manufacturing applications
- Select AI component technologies for implementing robotic cells for finishing applications
Who Should Attend
Company Management, Manufacturing Engineering, Production Engineering, Manufacturing Production, Researchers