Estimation and exploitation of objects' inertial parameters in robotic grasping and manipulation: A survey

被引:38
作者
Mavrakis, Nikos [1 ]
Stolkin, Rustam [2 ]
机构
[1] Univ Surrey, Surrey Space Ctr, STAR Lab, Guildford, Surrey, England
[2] Univ Birmingham, Extreme Robot Lab, Birmingham, W Midlands, England
基金
欧盟地平线“2020”; 英国工程与自然科学研究理事会;
关键词
Robot identification; Inertial parameters; Object dynamics; Robot grasping and manipulation; IDENTIFICATION METHOD; IMPEDANCE CONTROL; MASS ESTIMATION; PERCEPTION; VOLUME; TENSOR; STABILITY; CONTACT; FRUITS; HANDS;
D O I
10.1016/j.robot.2019.103374
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Inertial parameters characterise an object's motion under applied forces, and can provide strong priors for planning and control of robotic actions to manipulate the object. However, these parameters are not available a-priori in situations where a robot encounters new objects. In this paper, we describe and categorise the ways that a robot can identify an object's inertial parameters. We also discuss grasping and manipulation methods in which knowledge of inertial parameters is exploited in various ways. We begin with a discussion of literature which investigates how humans estimate the inertial parameters of objects, to provide background and motivation for this area of robotics research. We frame our discussion of the robotics literature in terms of three categories of estimation methods, according to the amount of interaction with the object: purely visual, exploratory, and fixed-object. Each category is analysed and discussed. To demonstrate the usefulness of inertial estimation research, we describe a number of grasping and manipulation applications that make use of the inertial parameters of objects. The aim of the paper is to thoroughly review and categorise existing work in an important, but under-explored, area of robotics research, present its background and applications, and suggest future directions. Note that this paper does not examine methods of identification of the robot's inertial parameters, but rather the identification of inertial parameters of other objects which the robot is tasked with manipulating. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页数:12
相关论文
共 114 条
[1]   Weight perception and the haptic size weight illusion are functions of the inertia tensor [J].
Amazeen, EL ;
Turvey, MT .
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-HUMAN PERCEPTION AND PERFORMANCE, 1996, 22 (01) :213-232
[2]   Application of computer vision and support vector regression for weight prediction of live broiler chicken [J].
Amraei S. ;
Abdanan Mehdizadeh S. ;
Sallary S. .
Engineering in Agriculture, Environment and Food, 2017, 10 (04) :266-271
[3]  
[Anonymous], P S SIGN PROC IM ART
[4]  
[Anonymous], 1986, P IEEE INT C ROBOTIC, DOI DOI 10.1109/ROBOT.1986.1087650
[5]  
[Anonymous], P IEEE INT C ROB AUT
[6]  
[Anonymous], 2004, INT J INFORM ACQUISI
[7]  
[Anonymous], ROBOTICS RES
[8]  
[Anonymous], OCADO COURTS GLOBAL
[9]  
[Anonymous], P INT S ROB RES
[10]  
[Anonymous], P INT C COMP TECHN A