Name
Abstract | ||
|---|---|---|
This paper presents recent advances to the Affordance Template (AT) task description language. Affordance Templates provide standardized, easy-to-use tools for defining robot manipulation tasks that provide a high level of augmented reality capabilities to facilitate human-in-the-loop operation, but can also be used to support robot autonomy when coupled with various planning tools. While initially defined in terms of end effector waypoint sequences for bimanual robots, such as the NASA Valkyrie and Robonaut 2, this paper extends the original specification to support integrated mobile manipulation, object-centric template definitions, autonomous grasp determination, and integration with custom and off-the-shelf collision free motion planners. ATs have proved highly adaptable to new robots and new domains by both the authors and third-party groups, and have been used in numerous contexts for NASA, DOD, and industry. As such, we believe that the AT framework provides a strong foundation for robot development in multiple real-world contexts that can be increasingly built upon and expanded to meet the challenges of many new applications. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/ICRA46639.2022.9812082 | IEEE International Conference on Robotics and Automation |
DocType | Volume | Issue |
Conference | 2022 | 1 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stephen Hart | 1 | 12 | 1.90 |
| Ana Huaman Quispe | 2 | 4 | 1.45 |
| Michael W. Lanighan | 3 | 0 | 0.34 |
| Seth Gee | 4 | 1 | 1.04 |