This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder. This thesis addresses the problem of sensor-based skill composition for robotic assembly tasks.
Skills are robust, reactive strategies for executing recurring tasks in our domain.
Efficiently building skills requires simultaneously reducing robot programming complexity and increasing sensor integration, which are competing and contradictory goals. This thesis attacks the problem through development of sensorimotor primitives to generalize sensor integration, graphical programming environments to facilitate skill composition, and design integration for exploiting the primitive capabilities during task design. Force and vision based sensorimotor primitives are built to provide sensor integration for task domains, not task instances. Finally, design agent representations of the primitives inside the CAD environment interact with the task model and the programmer to assist in composing the skill program. Experimental results for six different assembly tasks demonstrate sensor-based skill execution and illustrate primitive reusability.