Robot Learning by Visual Observation
Aleksandar Vakanski, Farrokh Janabi-Sharifi
- 出版商: Wiley
- 出版日期: 2017-02-13
- 售價: $3,600
- 貴賓價: 9.5 折 $3,420
- 語言: 英文
- 頁數: 208
- 裝訂: Hardcover
- ISBN: 1119091802
- ISBN-13: 9781119091806
-
相關分類:
機器人製作 Robots
立即出貨 (庫存 < 3)
買這商品的人也買了...
-
$3,160$3,002 -
$590$502 -
$1,200$1,140 -
$620$490 -
$780$616 -
$580$452 -
$720$562 -
$480$379 -
$590$502 -
$580$458 -
$1,617Deep Learning (Hardcover)
-
$580$493 -
$500$395 -
$360$281 -
$580$458 -
$400$316 -
$474$450 -
$403Tensorflow:實戰Google深度學習框架
-
$260$234 -
$480$379 -
$590$502 -
$680$537 -
$320$250 -
$860$731 -
$590$460
相關主題
商品描述
This book presents programming by demonstration for robot learning from observations with a focus on the trajectory level of task abstraction
- Discusses methods for optimization of task reproduction, such as reformulation of task planning as a constrained optimization problem
- Focuses on regression approaches, such as Gaussian mixture regression, spline regression, and locally weighted regression
- Concentrates on the use of vision sensors for capturing motions and actions during task demonstration by a human task expert
商品描述(中文翻譯)
本書介紹了一種以示範編程為基礎的機器人學習方法,重點在於以軌跡層次的任務抽象為目標。
- 討論了任務重現的優化方法,例如將任務規劃重新定義為一個受限制的優化問題
- 專注於回歸方法,例如高斯混合回歸、樣條回歸和局部加權回歸
- 專注於使用視覺感測器捕捉人類任務專家在示範任務期間的運動和動作