触觉传感器
机械手
计算机科学
控制工程
极限(数学)
人工智能
工程类
人机交互
人工神经网络
机器人
夹持器
控制(管理)
接触力
控制系统
机器人学
机械手
机械臂
计算机视觉
触觉刺激
计算机硬件
模拟
数字
嵌入式系统
作者
Mike Lambeta,Po-Wei Chou,Stephen Tian,Brian Yang,Benjamin Maloon,Victoria Rose Most,Dave Stroud,Raymond Santos,Ahmad Byagowi,Gregg Kammerer,Dinesh Jayaraman,Roberto Calandra
标识
DOI:10.1109/lra.2020.2977257
摘要
Despite decades of research, general purpose in-hand manipulation remains one of the unsolved challenges of robotics. One of the contributing factors that limit current robotic manipulation systems is the difficulty of precisely sensing contact forces - sensing and reasoning about contact forces are crucial to accurately control interactions with the environment. As a step towards enabling better robotic manipulation, we introduce DIGIT, an inexpensive, compact, and high-resolution tactile sensor geared towards in-hand manipulation. DIGIT improves upon past vision-based tactile sensors by miniaturizing the form factor to be mountable on multi-fingered hands, and by providing several design improvements that result in an easier, more repeatable manufacturing process, and enhanced reliability. We demonstrate the capabilities of the DIGIT sensor by training deep neural network model-based controllers to manipulate glass marbles in-hand with a multi-finger robotic hand. To provide the robotic community access to reliable and low-cost tactile sensors, we open-source the DIGIT design at www.digit.ml.
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