Robot Programming without Coding
By Gianluca Lentini, Giorgio Grioli, Manuel Giuseppe Catalano, Antonio Bicchi. 2020
14 citations recorded by the source corpus.
An approach toward intuitive and easy robot programming, consists to transfer skills from humans to machines, through demonstration. A vast literature exists on learning from multiple demonstrations.This paper, on the other hand, tackles the problem of providing all needed information to execute a certain task by resorting to one single demonstration - hence, a problem closer to programming than to learning. We use wearable consumer devices - but no keyboard nor coding - as programming tools, to let the programmer tele-operate the robot, which in turn records the most salient features and affordances from the object, environment, robot, and human.To enable this goal we combine off-the-shelf soft-articulated robotic components with the framework of Dynamic Movement Primitives, which we contribute to extend to generalize human trajectories and impedance regulation skills.This framework enables to teach robot quickly and in a intuitive way without coding. Experimental tests have been performed on a dual-arm system composed by two 7-dofs collaborative robots equipped with anthropomorphic end-effectors. Experiments show the functionality of the framework and verify the effectiveness of the impedance extension.
Subfields: Artificial Intelligence, Control and Systems Engineering, Mechanical Engineering
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Yuke Zhu
- Li Fei-Fei
- Silvio Savarese
- Ajay Mandlekar
- Roberto Mart'in-Mart'in
- Abhinav Kumar Gupta
- Josiah Wong
- Trevor Darrell
In Control and Systems Engineering
- Yuke Zhu
- Ajay Mandlekar
- Li Fei-Fei
- Silvio Savarese
- Roberto Mart'in-Mart'in
- Josiah Wong
- Danfei Xu
- Linxi (Jim) Fan
In Mechanical Engineering
- Yuke Zhu
- Li Fei-Fei
- Ajay Mandlekar
- Silvio Savarese
- Roberto Mart'in-Mart'in
- Josiah Wong
- Linxi (Jim) Fan
- Danfei Xu
Citations in the corpus
- Learning Multi-Arm Manipulation Through Collaborative Teleoperation (2020, background): “Some prior works [13, 21, 33, 43] have leveraged the paradigm of programming by demonstration, but these approaches often requires large modeling assumptions, and may not generalize well to different environment configurations.”