Learning force sensory patterns and skills front human demonstration
نویسندگان
چکیده
The motivation behind this work is to transfer force-based assembly skills to robots by using human demonstration. For this purpose, we model the skills as a sequence of contact formations (which describe how a workpiece touches its environment) and desired transitions between contact formations. In this paper , we present a method of identifying single-ended contact formations from force sensor patterns. Instead of using geometric models of the workpieces, fuzzy logic is used to learn and model the patterns in the force signals. Membership functions are generated automatically from training data and then used by the fuzzy classiier. This classiication scheme is used to learn desired sequences of contact formations which comprise a force-based skill. Experimental results are presented which use the technique to extract skill information from human demonstration data.
منابع مشابه
Comparison of Video-Based Instruction and Instructor Demonstration on Learning of Practical Skills in Nursing Students
Introduction: Since technology has an important role in the improvement of educational quality, finding better methods of teaching and learning and improving equipment and teaching materials is emphasized. Regarding this, two educational methods- presentation by the instructor and video presentation, were offered and their effectiveness on nursing students’ learning skills was compared. Method...
متن کاملIdentifying contact formations from sensory patterns and its applicability to robot programming by demonstration
This paper presents a pattern recognition approach to identifying contact formations from force sensor signals. The approach is sensor-based and does not use geometric models of the workpieces. The design of a fuzzy classiier is described, where membership functions are generated automatically from training data. The technique is demonstrated using supervised learning. Test results are included...
متن کاملBehavior Recognition for Segmentation of Demonstrated Tasks
One common approach to the robot learning technique Learning From Demonstration, is to use a set of preprogrammed skills as building blocks for more complex tasks. One important part of this approach is recognition of these skills in a demonstration comprising a stream of sensor and actuator data. In this paper, three novel techniques for behavior recognition are presented and compared. The fir...
متن کاملLearning Force-Based Assembly Skills from Human Demonstration for Execution in Unstructured Environments
Robots have been used successfully in structured settings , where the environment is controlled; this research is inspired by the vision of robots moving beyond the structured, controlled settings. The work fo-cuses on the problem of learning low-level force-based assembly skills from human demonstration. To avoid position dependencies, force-based discrete states are used to describe qualitati...
متن کاملRobot Learning from Demonstration in the Force Domain
Researchers are becoming aware of the importance of other information sources besides visual data in robot learning by demonstration (LbD). Forcebased perceptions are shown to convey very relevant information – missed by visual and position sensors – for learning specific tasks. In this paper, we review some recent works using forces as input data in LbD and Human-Robot interaction (HRI) scenar...
متن کامل