Dextrous hand grasping strategies using preshapes and digit trajectories:
Abstract: "Inspired by human grasping behavior, use of hand preshapes has for some time been recognized as a useful way of reducing the complexity of planning grasps for a dextrous hand. We define four types of task-specific preshape and two modes of digit closure, and give criteria for the cho...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Edinburgh
1995
|
| Series: | University <Edinburgh> / Department of Artificial Intelligence: DAI research paper
768 |
| Subjects: | |
| Summary: | Abstract: "Inspired by human grasping behavior, use of hand preshapes has for some time been recognized as a useful way of reducing the complexity of planning grasps for a dextrous hand. We define four types of task-specific preshape and two modes of digit closure, and give criteria for the choice and positioning of the preshapes, based on intersecting digit trajectories with the graspable surfaces of the object. Grasps are planned in simulation using real range data from a laser striper and an anthropomorphic hand model. Our results show that a range of polyhedral and curved objects can be grasped using relatively simple, fast algorithms when the hand movements are constrained in this way." |
| Physical Description: | [7] S. |
Staff View
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| 100 | 1 | |a Wren, David |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Dextrous hand grasping strategies using preshapes and digit trajectories |c Wren, D. ; Fisher, R. B. |
| 264 | 1 | |a Edinburgh |c 1995 | |
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| 490 | 1 | |a University <Edinburgh> / Department of Artificial Intelligence: DAI research paper |v 768 | |
| 520 | 3 | |a Abstract: "Inspired by human grasping behavior, use of hand preshapes has for some time been recognized as a useful way of reducing the complexity of planning grasps for a dextrous hand. We define four types of task-specific preshape and two modes of digit closure, and give criteria for the choice and positioning of the preshapes, based on intersecting digit trajectories with the graspable surfaces of the object. Grasps are planned in simulation using real range data from a laser striper and an anthropomorphic hand model. Our results show that a range of polyhedral and curved objects can be grasped using relatively simple, fast algorithms when the hand movements are constrained in this way." | |
| 650 | 7 | |a Bionics and artificial intelligence |2 sigle | |
| 650 | 7 | |a Pattern recognition, image processing and remote sensing |2 sigle | |
| 650 | 7 | |a Robotics and its application |2 sigle | |
| 650 | 4 | |a Hand |x Simulation methods | |
| 650 | 4 | |a Movement sequences | |
| 700 | 1 | |a Fisher, Robert B. |e Verfasser |4 aut | |
| 810 | 2 | |a Department of Artificial Intelligence: DAI research paper |t University <Edinburgh> |v 768 |w (DE-604)BV010450646 |9 768 | |
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Record in the Search Index
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| author | Wren, David Fisher, Robert B. |
| author_facet | Wren, David Fisher, Robert B. |
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| author_sort | Wren, David |
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| building | Verbundindex |
| bvnumber | BV011045479 |
| ctrlnum | (OCoLC)35171294 (DE-599)BVBBV011045479 |
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| id | DE-604.BV011045479 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-09T18:03:06Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-007396541 |
| oclc_num | 35171294 |
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| owner_facet | DE-91G DE-BY-TUM |
| physical | [7] S. |
| publishDate | 1995 |
| publishDateSearch | 1995 |
| publishDateSort | 1995 |
| record_format | marc |
| series2 | University <Edinburgh> / Department of Artificial Intelligence: DAI research paper |
| spelling | Wren, David Verfasser aut Dextrous hand grasping strategies using preshapes and digit trajectories Wren, D. ; Fisher, R. B. Edinburgh 1995 [7] S. txt rdacontent n rdamedia nc rdacarrier University <Edinburgh> / Department of Artificial Intelligence: DAI research paper 768 Abstract: "Inspired by human grasping behavior, use of hand preshapes has for some time been recognized as a useful way of reducing the complexity of planning grasps for a dextrous hand. We define four types of task-specific preshape and two modes of digit closure, and give criteria for the choice and positioning of the preshapes, based on intersecting digit trajectories with the graspable surfaces of the object. Grasps are planned in simulation using real range data from a laser striper and an anthropomorphic hand model. Our results show that a range of polyhedral and curved objects can be grasped using relatively simple, fast algorithms when the hand movements are constrained in this way." Bionics and artificial intelligence sigle Pattern recognition, image processing and remote sensing sigle Robotics and its application sigle Hand Simulation methods Movement sequences Fisher, Robert B. Verfasser aut Department of Artificial Intelligence: DAI research paper University <Edinburgh> 768 (DE-604)BV010450646 768 |
| spellingShingle | Wren, David Fisher, Robert B. Dextrous hand grasping strategies using preshapes and digit trajectories Bionics and artificial intelligence sigle Pattern recognition, image processing and remote sensing sigle Robotics and its application sigle Hand Simulation methods Movement sequences |
| title | Dextrous hand grasping strategies using preshapes and digit trajectories |
| title_auth | Dextrous hand grasping strategies using preshapes and digit trajectories |
| title_exact_search | Dextrous hand grasping strategies using preshapes and digit trajectories |
| title_full | Dextrous hand grasping strategies using preshapes and digit trajectories Wren, D. ; Fisher, R. B. |
| title_fullStr | Dextrous hand grasping strategies using preshapes and digit trajectories Wren, D. ; Fisher, R. B. |
| title_full_unstemmed | Dextrous hand grasping strategies using preshapes and digit trajectories Wren, D. ; Fisher, R. B. |
| title_short | Dextrous hand grasping strategies using preshapes and digit trajectories |
| title_sort | dextrous hand grasping strategies using preshapes and digit trajectories |
| topic | Bionics and artificial intelligence sigle Pattern recognition, image processing and remote sensing sigle Robotics and its application sigle Hand Simulation methods Movement sequences |
| topic_facet | Bionics and artificial intelligence Pattern recognition, image processing and remote sensing Robotics and its application Hand Simulation methods Movement sequences |
| volume_link | (DE-604)BV010450646 |
| work_keys_str_mv | AT wrendavid dextroushandgraspingstrategiesusingpreshapesanddigittrajectories AT fisherrobertb dextroushandgraspingstrategiesusingpreshapesanddigittrajectories |