| 000 | 08257naaaa2202485uu 4500 | ||
|---|---|---|---|
| 003 | BUT | ||
| 005 | 20230405101848.0 | ||
| 006 | m o d | ||
| 007 | cr|mn|---annan | ||
| 008 | 20210211s2020 xx |||||o ||| eng|| d | ||
| 020 | _a9783039219452 | ||
| 020 | _a9783039219445 | ||
| 040 |
_aoapen _coapen |
||
| 041 | 0 | _aeng | |
| 080 | _a004 | ||
| 100 | 1 |
_aKim, DaeEun _4auth |
|
| 245 | 1 | 0 | _aAdvanced Mobile Robotics: Volume 2 |
| 260 |
_bMDPI - Multidisciplinary Digital Publishing Institute _c2020 |
||
| 300 | _a1 electronic resource (498 p.) | ||
| 506 | 0 |
_aOpen Access _2star _fUnrestricted online access |
|
| 520 | _aMobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective. | ||
| 540 |
_aCreative Commons _fhttps://creativecommons.org/licenses/by-nc-nd/4.0/ _2cc |
||
| 546 | _aEnglish | ||
| 650 | 0 |
_94541 _aРобототехника |
|
| 653 | _asimilarity measure | ||
| 653 | _aswarm-robotics | ||
| 653 | _adrag-based system | ||
| 653 | _aPID algorithm | ||
| 653 | _ahuman–robot interaction | ||
| 653 | _abehaviour dynamics | ||
| 653 | _astate constraints | ||
| 653 | _afair optimisation | ||
| 653 | _amicro mobile robot | ||
| 653 | _arobot | ||
| 653 | _aactuators | ||
| 653 | _ahigh-gain observer | ||
| 653 | _aturning model LIP | ||
| 653 | _aspace robot | ||
| 653 | _amanipulation action sequences | ||
| 653 | _asubgoal graphs | ||
| 653 | _aremotely operated vehicle | ||
| 653 | _aconstrained motion | ||
| 653 | _ajoint limit avoidance | ||
| 653 | _acurvilinear obstacle | ||
| 653 | _arehabilitation system | ||
| 653 | _astability criterion | ||
| 653 | _asystem design | ||
| 653 | _aquad-tilt rotor | ||
| 653 | _aiterative learning | ||
| 653 | _aspiral curve | ||
| 653 | _acable detection | ||
| 653 | _aSEA | ||
| 653 | _adouglas–peuker polygonal approximation | ||
| 653 | _apredictable trajectory planning | ||
| 653 | _aATEX | ||
| 653 | _aobstacle avoidance system | ||
| 653 | _akinematic singularity | ||
| 653 | _acollision avoidance | ||
| 653 | _abiologically-inspired | ||
| 653 | _ajumping robot | ||
| 653 | _adifferential wheeled robot | ||
| 653 | _adesign and modeling | ||
| 653 | _acontrol efficacy | ||
| 653 | _arobotics | ||
| 653 | _aextremum-seeking | ||
| 653 | _aobject-oriented | ||
| 653 | _anon-holonomic mobile robot | ||
| 653 | _amagneto-rheological fluids | ||
| 653 | _arendezvous consensus | ||
| 653 | _aaltitude controller | ||
| 653 | _amaster-slave | ||
| 653 | _aswitching control | ||
| 653 | _adeep reinforcement learning | ||
| 653 | _amechanism | ||
| 653 | _aexpansion logic strategy | ||
| 653 | _anegative buoyancy | ||
| 653 | _aaction generation | ||
| 653 | _aradial basis function neural networks | ||
| 653 | _aunmanned aerial vehicles | ||
| 653 | _aextend procedure | ||
| 653 | _aglass façade cleaning robot | ||
| 653 | _aconvolutional neural network | ||
| 653 | _aclimbing robot | ||
| 653 | _amicro air vehicle | ||
| 653 | _acar-like kinematics | ||
| 653 | _avariable speed | ||
| 653 | _amachine learning | ||
| 653 | _adynamical model | ||
| 653 | _atransportation | ||
| 653 | _ageodesic | ||
| 653 | _aunmanned surface vessel | ||
| 653 | _amedical devices | ||
| 653 | _astopper | ||
| 653 | _aextended state observer (ESO) | ||
| 653 | _ahigh efficiency | ||
| 653 | _aobject mapping | ||
| 653 | _amulti-objective optimization | ||
| 653 | _ahybrid robot | ||
| 653 | _arobot learning | ||
| 653 | _aauto-tuning | ||
| 653 | _acable disturbance modeling | ||
| 653 | _amanipulation planning | ||
| 653 | _apesticide application | ||
| 653 | _ahigh-speed target | ||
| 653 | _asparse pose adjustment (SPA) | ||
| 653 | _aservice robot | ||
| 653 | _alumped parameter method | ||
| 653 | _aGeometric Algebra | ||
| 653 | _adynamic coupling analysis | ||
| 653 | _aThau observer | ||
| 653 | _atri-tilt-rotor | ||
| 653 | _aindustrial robotic manipulator | ||
| 653 | _ahardware-in-the-loop simulation | ||
| 653 | _arobotic drilling | ||
| 653 | _amuscle activities | ||
| 653 | _asmall size | ||
| 653 | _achameleon | ||
| 653 | _acontinuous hopping | ||
| 653 | _awall climbing robot | ||
| 653 | _ahover mode | ||
| 653 | _a3D-SLAM | ||
| 653 | _acurvature constraints | ||
| 653 | _aPSO | ||
| 653 | _adrilling end-effector | ||
| 653 | _aRodrigues parameters | ||
| 653 | _agait adaptation | ||
| 653 | _astatic environments | ||
| 653 | _aposition/force cooperative control | ||
| 653 | _asnake-like robot | ||
| 653 | _ashape-fitting | ||
| 653 | _apowered exoskeleton | ||
| 653 | _ainput saturation | ||
| 653 | _akinematic identification | ||
| 653 | _amethane | ||
| 653 | _ahuman–machine interactive navigation | ||
| 653 | _aq-learning | ||
| 653 | _apath following | ||
| 653 | _ahopping robot | ||
| 653 | _amobile manipulation | ||
| 653 | _ahigh step-up ratio | ||
| 653 | _aactuatorless | ||
| 653 | _amonocular vision | ||
| 653 | _astability analysis | ||
| 653 | _acompact driving unit | ||
| 653 | _asnake robot | ||
| 653 | _anon-holonomic robot | ||
| 653 | _acurvature constraint | ||
| 653 | _aphase-shifting | ||
| 653 | _adialytic elimination | ||
| 653 | _agesture recognition | ||
| 653 | _asnake robots | ||
| 653 | _aseries elastic actuator | ||
| 653 | _aflapping | ||
| 653 | _aservo valve | ||
| 653 | _amotion camouflage control | ||
| 653 | _abiomimetic robot | ||
| 653 | _aminimally invasive surgery robot | ||
| 653 | _acentralized architecture | ||
| 653 | _atrajectory planning | ||
| 653 | _acomputing time | ||
| 653 | _aadaptive control law | ||
| 653 | _akinematics | ||
| 653 | _afacial and gender recognition | ||
| 653 | _asingle actuator | ||
| 653 | _avictim-detection | ||
| 653 | _ashape memory alloys | ||
| 653 | _aundiscovered sensor values | ||
| 653 | _adiscomfort | ||
| 653 | _aDifferential Evolution | ||
| 653 | _anumerical evaluation | ||
| 653 | _aquadruped robot | ||
| 653 | _acoverage path planning | ||
| 653 | _alocalization | ||
| 653 | _aMPC | ||
| 653 | _an/a | ||
| 653 | _afault diagnosis | ||
| 653 | _aneural networks | ||
| 653 | _adisturbance-rejection control | ||
| 653 | _asample gathering problem | ||
| 653 | _acart | ||
| 653 | _abio-inspired robot | ||
| 653 | _aopposite angle-based exact cell decomposition | ||
| 653 | _aoptimization | ||
| 653 | _asafety | ||
| 653 | _agoal exchange | ||
| 653 | _ahierarchical planning | ||
| 653 | _aocean current | ||
| 653 | _arobot motion | ||
| 653 | _anonlinear differentiator | ||
| 653 | _amapping | ||
| 653 | _afinite-time currents observer | ||
| 653 | _aNewton iteration | ||
| 653 | _ainverse kinematics | ||
| 653 | _adeposition uniformity | ||
| 653 | _aspatial pyramid pooling | ||
| 653 | _ahierarchical path planning | ||
| 653 | _aend effector | ||
| 653 | _ahead-raising | ||
| 653 | _afault recovery | ||
| 653 | _aLOS | ||
| 653 | _apath tracking | ||
| 653 | _anon-inertial reference frame | ||
| 653 | _astep climbing | ||
| 653 | _aobstacle avoidance | ||
| 653 | _asliding mode control | ||
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://mdpi.com/books/pdfview/book/2068 _70 _zDownload |
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/40203 _70 _zDescription |
| 909 |
_c4 _dDarya Shvetsova |
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| 942 |
_2udc _cEE |
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