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
- 2009.8
- 수록면
- 4,530 - 4,535 (6page)
이용수
초록· 키워드
오류제보하기
An iterative method using the neural networks to solve the inverse kinematics problem for equal length links redundant manipulators is presented in this paper. The training phase, calculating the neural networks weights, is accomplished for a new proposed geometrical method to solve the problem of multi-solution caused by redundancy. The use of this geometrical method results in one solution among the infinite solutions of the inverse kinematics of theredundant manipulators. This method is very effective for avoiding the singularity problem because it guarantees that there is no lining up for two or more links. Another advantage for this method is that the angles between the links willbe set between two maximum and minimum values. This means that the end-effecter can reach any point on the desired path and the angles between the links will not be less than the minimum limit or more than the maximum limit, which makes this method effective for joint limits. To demonstrate the effectiveness of this proposed method, experiments were conducted on an 8 links hyper redundant manipulator in this paper. In addition, the workspace of the manipulator is calculated for this proposed method.
목차
Abstract
1. INTRODUCTION
2. THE NEURAL NETWORKS TOPOLOGY AND THE LEARNING METHOD
3. THE GEOMETRICAL METHOD FOR THE INVERSE KINEMATICS
4. MINIMUM AND MAXIMUM REACH OF THE MANIPULATOR
5. WORKSPACE OF THE PROPOSED METHOD
6. SINGULARITY AVOIDANCE
6. SIMULATION RESULTS
7. CONCLUSION
REFERENCES
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UCI(KEPA) : I410-ECN-0101-2014-569-000760742