Investigating the Impact of Robot Degree of Redundancy on Learning from Demonstration

Abstract

Learning from Demonstration allows robots to acquire skills from human demonstrations, making them more accessible to a wider range of users. Among different approaches, kinesthetic teaching allows humans to manipulate the robot joints directly, making it effective method for demonstrating constrained tasks. However, robots with kinematic redundancy enable multiple joint configurations to achieve a desired task, which could influence human teaching performance. One one hand, it could make it easier, allowing more freedom to demonstrate the task, but on the other, it also increases the number of joints that needs to be manipulated, potentially affecting cognitive and physical load of the demo..