Title :
Learning robot motion control with demonstration and advice-operators
Author :
Argall, Brenna D. ; Browning, Brett ; Veloso, Manuela
Author_Institution :
Comput. Sci. Dept., Carnegie Mellon Univ., Pittsburgh, PA
Abstract :
As robots become more commonplace within society, the need for tools to enable non-robotics-experts to develop control algorithms, or policies, will increase. Learning from demonstration (LfD) offers one promising approach, where the robot learns a policy from teacher task executions. Our interests lie with robot motion control policies which map world observations to continuous low-level actions. In this work, we introduce advice-operator policy improvement (A-OPI) as a novel approach for improving policies within LfD. Two distinguishing characteristics of the A-OPI algorithm are data source and continuous state-action space. Within LfD, more example data can improve a policy. In A-OPI, new data is synthesized from a student execution and teacher advice. By contrast, typical demonstration approaches provide the learner with exclusively teacher executions. A-OPI is effective within continuous state-action spaces because high level human advice is translated into continuous-valued corrections on the student execution. This work presents a first implementation of the A-OPI algorithm, validated on a Segway RMP robot performing a spatial positioning task. A-OPI is found to improve task performance, both in success and accuracy. Furthermore, performance is shown to be similar or superior to the typical exclusively teacher demonstrations approach.
Keywords :
intelligent robots; learning systems; mobile robots; motion control; position control; Segway RMP robot; advice-operator policy improvement; continuous state-action space; learning from demonstration; learning robot motion control; spatial positioning task; teacher task executions; Accuracy; Humans; Mobile robots; Robot motion; Robot sensing systems; Robots; Sensors;
Conference_Titel :
Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on
Conference_Location :
Nice
Print_ISBN :
978-1-4244-2057-5
DOI :
10.1109/IROS.2008.4651020