지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 1992.10
- 수록면
- 564 - 568 (5page)
이용수
이 논문의 연구 히스토리 (2)
1992
Neural Optimization networks with Fuzzy Weighting for Collision Free motions of Redundant Robot Manipulators
Woong Keun Hyun
,
Il Hong Suh
,
Kyong Gi kim
대한전자공학회 학술대회
1992.10
학술대회자료
Neural Optimization networks with Fuzzy Weighthin for Collision Free motions of Redundant Robot Manipulators
Woong Keun Hyun
,
Il Hong Suh
,
Kyong Gi kim
제어로봇시스템학회 국내학술대회 논문집
1992.10
학술대회자료
- 이 논문의 후속연구가 궁금하신가요?
- 연관 학술논문 또는 학술발표를 통해 보다 발전된 연구결과를 확인하실 수 있습니다.
- 이 논문의 연구 히스토리 확인하기
초록· 키워드
오류제보하기
A neural optimization network is designed to solve the collision-free inverse kinematics problem for redundant robot manipulators under the constraints of joint limits, maximum velocities and maximum accelerations. And the fuzzy rules are proposed to determine the weightings of neural optimization networks to avoid the collision between robot manipulator and obstacles. The inputs of fuzzy rules are the resultant distance, change of the distance and sum of the changes. And the output of fuzzy rules is defined as the capability of collision avoidance of joint differential motion. The weightings of neural optimization networks are adjusted according to the capability of collision avoidance of each joint.
To show the validities of the proposed method, computer simulation results are illustrated for the redundant robot with three degrees of freedom.
To show the validities of the proposed method, computer simulation results are illustrated for the redundant robot with three degrees of freedom.
목차
ABSTRACT
1. INTRODUCTION
2. A NEURAL OPTIMIZATION NETWORK FOR COLLISION AVOIDANCE OF REDUNDANT ROBOT
3. DETERMINATION OF WEIGHTiNGS FOR THE COLLISION AVOIDANCE
4. SIMULATION RESULTS
5. CONCLUSIONS
REFERENCES
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