Name
Abstract | ||
|---|---|---|
We address the problem of transferring grasp knowledge across objects and tasks. This means dealing with two important issues: 1) the induction of possible transfers, i.e., whether a given object affords a given task, and 2) the planning of a grasp that will allow the robot to fulfill the task. The induction of object affordances is approached by abstracting the sensory input of an object as a set of attributes that the agent can reason about through similarity and proximity. For grasp execution, we combine a part-based grasp planner with a model of task constraints. The task constraint model indicates areas of the object that the robot can grasp to execute the task. Within these areas, the part-based planner finds a hand placement that is compatible with the object shape. The key contribution is the ability to transfer task parameters across objects while the part-based grasp planner allows for transferring grasp information across tasks. As a result, the robot is able to synthesize plans for previously unobserved task/object combinations. We illustrate our approach with experiments conducted on a real robot. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICRA.2014.6907697 | Robotics and Automation |
Keywords | Field | DocType |
path planning,robots,cross-object grasp transfer,cross-task grasp transfer,hand placement,part-based grasp planner,sensory input,task constraint | GRASP,Robot path planning,Artificial intelligence,Engineering | Conference |
Volume | Issue | ISSN |
2014 | 1 | 1050-4729 |
Citations | PageRank | References |
3 | 0.39 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin Hjelm | 1 | 7 | 1.51 |
| Renaud Detry | 2 | 183 | 13.94 |
| carl henrik ek | 3 | 327 | 30.76 |
| Danica Kragic | 4 | 2070 | 142.17 |