查詢結果分析
來源資料
相關文獻
- 機器人定位精度的校準
- 機器人定位精度的校準
- 機器人定位量測裝置應用之比較
- Development of a Sensory Data Glove Using Neural-Network-Based Calibration
- 基於直方圖更新之混合粒子濾波法於追隨機器人之應用
- A Robotic Planning Navigation System for Surgical Positioning and Drilling
- Quantitative Comparison between Artificial Neural Networks and Bilinear Interpolation to Predict a Real Robot's Sonar Sensor Readings
- 基于雲端運算之多機器人控制方法應用於垃圾清潔問題
- Neural Network Procedures for Taguchi's Dynamic Problems
- A Fast and Efficient Competitive Learning Design Algorithm Based on Weight Vector Training in Transform Domain
頁籤選單縮合
| 題 名 | 機器人定位精度的校準=The Calibration of Robot Positioning Accuracy |
|---|---|
| 作 者 | 李松賢; 曾清秀; 陳振山; | 書刊名 | 技術學刊 |
| 卷 期 | 12:3 1997.09[民86.09] |
| 頁 次 | 頁383-392 |
| 分類號 | 448.94 |
| 關鍵詞 | 機器人; 校準; 類神經網路; Robot; Calibration; Artificial neural network; ANN; |
| 語 文 | 中文(Chinese) |
| 中文摘要 | 機器人的校準研究,大都只考慮幾何誤差模式,忽略非幾何誤差的影響,本研 究將整合幾何與非幾何誤差模式以提高機器人的定位精度。在幾何模式方面,考慮二階以 下的誤差項,並將各連桿的誤差參數,以類神經網路構建成為後三軸位置誤差的補償器; 在非幾何誤差方面,利用經緯儀來量測前三軸位置誤差的資料,再利用類神經網路將資料 訓練成為方位誤差補償器。最後利用經緯儀加以量測驗證輸出合成位置的補償量,結果證 實能提高機器人的定位精度。 |
| 英文摘要 | Most research on robot calibration has considered only the model of geometric error, and neglected the effect of nongeometric error. This work integrates both geometric and nongeometric error models to improve robot positioning accuracy. In the geometric model, the first and second order error terms are considered, and the error parameters of the links are used to built a position error compensator for the last three axes. As to nongeometric error, we use two theodolites to measure the position error of the first three axes. These error data are then used to train the neural network of the error compensator. Finally, this study is verified using theodolite and it shows that the robot positioning accuracy can be improved. |
本系統中英文摘要資訊取自各篇刊載內容。