Name
Abstract | ||
|---|---|---|
Addresses the grasp synthesis problem arising in task planning for robotic dextrous hands. For this purpose, a hybrid architecture is proposed, which relies on symbolic and subsymbolic computations to exploit heterogeneous sources of knowledge, such as practical experience learned through experiments with a real device, heuristic rules gained from human observation, geometric reasoning and, when applicable, analytical results. After a preliminary discussion of representation levels and techniques, this paper describes the design of a tool for selecting the feasible grasps of a robotic hand under various situations and for ranking them according to task-oriented criteria. The interaction of a rule-based expert system with a neural network-based classifier provides support to both explicit reasoning and direct learning from experience. The features taken into account by the tool are object geometry, hand kinematic capabilities, task requirements, (in terms of both accessibility and robustness) and workspace constraints |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1109/IROS.1993.583849 | Intelligent Robots and Systems '93, IROS '93. Proceedings of the 1993 IEEE/RSJ International Conference |
Keywords | Field | DocType |
path planning,accessibility,analytical results,direct learning from experience,explicit reasoning,geometric reasoning,grasp synthesis,hand kinematic capabilities,heuristic rules,human observation,hybrid system,knowledge-based synthesis,neural network-based classifier,object geometry,practical experience,ranking,representation levels,robotic dextrous hands,robustness,rule-based expert system,subsymbolic computations,task planning,task requirements,task-oriented criteria,workspace constraints | Motion planning,Heuristic,GRASP,Computer science,Workspace,Expert system,Robustness (computer science),Artificial intelligence,Hybrid system,Machine learning,Legal expert system | Conference |
Volume | ISBN | Citations |
3 | 0-7803-0823-9 | 2 |
PageRank | References | Authors |
0.47 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefano Caselli | 1 | 2 | 0.47 |
| Eugenio Faldella | 2 | 5 | 3.34 |
| Bruno Fringuelli | 3 | 2 | 0.47 |
| Francesco Zanichelli | 4 | 31 | 2.68 |