Development of a Simulator of Environment and Measurement for Multiple Autonomous Mobile Robots Considering Camera Characteristics

Umeda, Kazunori; Asanuma, Kazunori; Kikuchi, T.; Ueda, Ryuichi; Osumi, Hisashi; Arai, Tamio

doi:10.7210/jrsj.23.878

Search citation statements

Order By: Relevance

Paper Sections

Select...

Fuzzy Rule For Inverse Kinematics1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2007

2012

Publication Types

Select...

Article1

Book1

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 5 shows a photograph of the robot used in the experiment and the hardware configuration. The lower body is an autonomous 10 DOF humanoid robot with a 16-bit microprocessor [8][9][10][11][12]. However, we have defined the leg to consist of 3 DOF, and, therefore, 6 DOF in total are controlled.…”

Section: Fuzzy Rule For Inverse Kinematicsmentioning

confidence: 99%

Integer inverse kinematics method using Fuzzy logic

Morishita

Tojo

2012

Intel Serv Robotics

View full text Add to dashboard Cite

In this paper, we propose an integer inverse kinematics method for multijoint robot control. The method reduces computational overheads and leads to the development of a simple control system as the use of fuzzy logic enables linguistic modeling of the joint angle. A small humanoid robot is used to confirm via experiment that the method produces the same cycling movements in the robot as those in a human. In addition, we achieve fast information sharing by implementing the all-integer control algorithm in a low-cost, low-power microprocessor. Moreover, we evaluate the ability of this method for trajectory generation and confirm that target trajectories are reproduced well. The computational results of the general inverse kinematics model are compared to those of the integer inverse kinematics model and similar outputs are demonstrated. We show that the integer inverse kinematics model simplifies the control process.

show abstract

Section: Fuzzy Rule For Inverse Kinematicsmentioning

confidence: 99%