A genetic algorithm based area coverage approach for controlled drug delivery using micro-robots

被引:0
|
作者
Tao, WM [1 ]
Zhang, MJ [1 ]
Tarn, TJ [1 ]
机构
[1] Brooks Automat Inc, Mountain View, CA USA
关键词
genetic algorithm; area coverage; drug delivery; tumor treatment; micro-robots;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper describes a Genetic Algorithm (GA) based approach for area coverage using micro-robots. The method can be used for controlled drug delivery or tumor treatment using micro-robots. The algorithm aims to find a near-optimal path that covers a given area entirely, except obstacles defined as biological barriers or drug side effect restricted zones. The proposed GA approach is a dynamic online path planning approach, which is able to achieve planning during motion and to response to detected obstacles. Different from point-to-point path planning, the proposed operators for the GA are specially designed for area coverage. Comparisons of the approach with high-level static optimal search algorithms and low-level fixed path planning approaches are also presented. Simulation results are given to show the effectiveness of the approach.
引用
收藏
页码:2086 / 2091
页数:6
相关论文
共 50 条
  • [21] Genetic Engineering of Protein-Based Polymers: Potential in Controlled Drug Delivery
    Hamidreza Ghandehari
    Joseph Cappello
    Pharmaceutical Research, 1998, 15 : 813 - 815
  • [22] Learning Area Coverage for a Self-Sufficient Hexapod Robot Using a Cyclic Genetic Algorithm
    Parker, Gary
    Zbeda, Richard
    IEEE SYSTEMS JOURNAL, 2014, 8 (03): : 778 - 790
  • [23] Sensor Placement Based on an Improved Genetic Algorithm for Connected Confident Information Coverage in an Area with Obstacles
    Dai, Lu
    Wang, Bang
    2017 IEEE 42ND CONFERENCE ON LOCAL COMPUTER NETWORKS (LCN), 2017, : 595 - 598
  • [24] MOTION PLANNING OF SWARM ROBOTS USING POTENTIAL-BASED GENETIC ALGORITHM
    Lin, Chien-Chou
    Chen, Kun-Cheng
    Hsiao, Po-Yuan
    Chuang, Wei-Ju
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2013, 9 (01): : 305 - 318
  • [25] Markov approach for quantifying the software code coverage using genetic algorithm in software testing
    Boopathi, M.
    Sujatha, R.
    Kumar, C. Senthil
    Narasimman, S.
    Rajan, A.
    INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION, 2019, 14 (01) : 27 - 45
  • [26] Total Coverage Based Regression Test Case Prioritization using Genetic Algorithm
    Konsaard, Patipat
    Ramingwong, Lachana
    2015 12TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING/ELECTRONICS, COMPUTER, TELECOMMUNICATIONS AND INFORMATION TECHNOLOGY (ECTI-CON), 2015,
  • [27] A Complete Coverage Path Planning Algorithm for Cleaning Robots Based on the Distance Transform Algorithm and the Rolling Window Approach in Dynamic Environments
    Zhou, Yongzheng
    Sun, Rongchuan
    Yu, Shumei
    Sun, Yong
    Sun, Lining
    2017 IEEE 7TH ANNUAL INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (CYBER), 2017, : 1335 - 1340
  • [28] An approach to wide area WDM optical network design using genetic algorithm
    Saha, D
    Purkayastha, MD
    Mukherjee, A
    COMPUTER COMMUNICATIONS, 1999, 22 (02) : 156 - 172
  • [29] Genetic engineering of protein-based polymers: Potential in controlled drug delivery - Commentary
    Ghandehari, H
    Cappello, J
    PHARMACEUTICAL RESEARCH, 1998, 15 (06) : 813 - 815
  • [30] Improving ATM coverage area using density based clustering algorithm and voronoi diagrams
    Kisore, N. Raghu
    Koteswaraiah, Ch. B.
    INFORMATION SCIENCES, 2017, 376 : 1 - 20