「自」能醫(yī)療微型機械人 群起如蜂
指南者留學
2022-06-23 14:55:17
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<div class="ace-line ace-line old-record-id-doxcn2W0gkku2ygKiI7TTz0f1Wd" style="text-align: justify;"><span class="p">在自然界,不難看見動物結(jié)隊躲避天敵或捕食獵物的集群行為,猶如有指揮官在背后發(fā)放指令。 香港中文大學機械與自動化工程學系<strong>張立教授</strong>的團隊多年來一直致力研發(fā)醫(yī)療微型機械人,受此啟發(fā),他聯(lián)同計算機科學與工程學系<strong>竇琪教授</strong>合作研發(fā)了一套微型機械人集群自動導(dǎo)航系統(tǒng)技術(shù),結(jié)合人工智能,讓機械人擁有自主導(dǎo)航能力。 它更會如蜜蜂般成群結(jié)隊工作,并因應(yīng)體內(nèi)環(huán)境自動改變隊形,于人體內(nèi)游走進行針對性的治療。</span></div>
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<div class="ace-line ace-line old-record-id-doxcnEcKMs2Ki0WqWcTa5acf4Sf" style="text-align: justify;"><span class="p">現(xiàn)時微型機械人大多以個體模式行動,優(yōu)點是體積細小,但容量有限,每次只能輸送有限藥物,要運載更多的份量,只有增加機械人的數(shù)量。 但另一問題是人體內(nèi)盡是蜿蜒曲折的腔道、流動的液體,很難實時控制成千上萬個機械人同步執(zhí)行任務(wù)。 縱使可以利用外部磁場引領(lǐng)機械人,或以硬件作實時導(dǎo)航及定位配合來控制機械人的行動,但都難免出現(xiàn)機械人失誤或不受控的情況。</span></div>
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<h2 class="heading-2 ace-line old-record-id-doxcn0kyGcCEo0Yg2QrCS4ZI5tf" style="text-align: justify;"><span class="p"><strong>人工智能系統(tǒng)發(fā)號施令</strong></span></h2>
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<div class="ace-line ace-line old-record-id-doxcnWCykU8OQiqEEGeky19fB5c" style="text-align: justify;"><span class="p">為了增加微型機械人集群的智力穩(wěn)定地執(zhí)行任務(wù),研究團隊結(jié)合過去多年研究微型機械人的經(jīng)驗,利用深度學習技術(shù),建立一套人工智能微型機械人操控系統(tǒng),增加機械人的自主運算及決策能力。 張教授表示:「我們集結(jié)了專業(yè)人員操作機械人的經(jīng)驗及知識去訓練智能系統(tǒng),賦予微型機械人集群的自主巡航能力,以助減少任務(wù)失誤的機會?!?lt;/span></div>
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<div class="ace-line ace-line old-record-id-doxcnmEMWge0umi2W4S2sBcGDld" style="text-align: justify;"><span class="p">微型機械人集群有五個級別的自主程度,由0級至4級; 0代表手動控制、4代表完全自主。 圖中紅色標志為需要人手輸入設(shè)定的參數(shù)項目; 綠色代表參數(shù)項目已達到自動化,由人工智能電腦運算控制。</span></div>
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<div class="ace-line ace-line old-record-id-doxcnyUGCqgWUWqEMOiNg9v5RKK" style="text-align: justify;"><span class="p">團隊設(shè)計的自動導(dǎo)航系統(tǒng)/深度學習系統(tǒng)Deep Neural Networks (DNN)可以按體內(nèi)環(huán)境實時運算出機械人的分布、移動軌跡、磁場、機械人群體的中心點及目標位置等參數(shù),讓微機械人懂得因應(yīng)不同環(huán)境而適時調(diào)整集群行動,按照精準的計劃路線完成任務(wù)。 團隊亦按照人體內(nèi)不同情境設(shè)定,如靜態(tài)或動態(tài)環(huán)境,將微機械人的自主程度分成五個級別; 級別愈高,要求手動控制的部分愈少。 操作人員可按需要及實際情境選擇機械人的自主模式。</span></div>
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<div class="ace-line ace-line old-record-id-doxcnuEsyGYAYGMQCgbLz2DKuqf" style="text-align: justify;"><span class="p">級別0類近現(xiàn)時大多數(shù)微型機械人的操作方式,機械人集群全以人手導(dǎo)航,操作人員必須接受充足的訓練,了解機械人的物理狀態(tài),以及熟悉系統(tǒng)的操作。 硬件上,亦需全程以光學顯微鏡等成像工具實時監(jiān)察機械人的行動,同步計劃及控制它們的集群形態(tài)、路線與目標位置等,避免機械人碰上障礙物。 不過,人手操作容易存在誤差,控制不良或會令微機械人集群偏離航道或分裂。</span></div>
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<div class="ace-line ace-line old-record-id-doxcneU60oyCIuYUGeSxDx8St9C" style="text-align: justify;"><span class="p">級別4的機械人集群可以做到全自主狀態(tài),能在復(fù)雜多變的動態(tài)環(huán)境中執(zhí)行醫(yī)療任務(wù)。 例如任務(wù)是將標靶藥物輸送到病灶,系統(tǒng)會自動及實時搜尋目標位置、規(guī)劃航道及機械人的集群形態(tài),直至完成任務(wù)。 如感應(yīng)到前方有障礙物,也能迅速重新規(guī)劃航道,過程中無須人手介入,能減省訓練專業(yè)操作員的成本。</span></div>
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<div class="ace-line ace-line old-record-id-doxcneeAmME6YsEuecOYPpAJoEQ" style="text-align: justify;"><span class="p">人類胎盤實驗于InnoHK(創(chuàng)新香港研發(fā)平臺),位于香港科學園的醫(yī)療機械人創(chuàng)新技術(shù)中心進行。 實驗平臺設(shè)有C-arm X光螢光鏡等成像工具作為機械人的「眼睛」,以偵測障礙物,作實時方向調(diào)整及導(dǎo)航。</span></div>
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<div class="ace-line ace-line old-record-id-doxcnGKcikEU4GC6OO04GfZCGNf" style="text-align: justify;"><span class="p">為了測試微型機械人集群在人工智能導(dǎo)航系統(tǒng)下的運作情況,研究團隊與韋爾斯親王醫(yī)院合作在人類胎盤樣本進行體外實驗,結(jié)果顯示導(dǎo)航系統(tǒng)能有效在血管這類復(fù)雜的體內(nèi)動態(tài)環(huán)境和微小且曲折的渠道內(nèi)為機械人集群導(dǎo)航。</span></div>
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<div class="ace-line ace-line old-record-id-doxcnC2wqoK6S4AoqCss9LJTeMd" style="text-align: justify;"><span class="p">張教授期望:「隨著自動導(dǎo)航系統(tǒng)技術(shù)的發(fā)展愈趨成熟,我們希望此人工智能控制系統(tǒng)可讓醫(yī)生在無需接受特別操作培訓下,利用微型機械人集群為病人進行無創(chuàng)或微創(chuàng)治療,特別是在深入體內(nèi)的曲折狹小腔體內(nèi)。」</span></div>
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<h2 class="heading-2 ace-line old-record-id-doxcnGSWMOgmkgAgycFx0bYkmIe" style="text-align: justify;"><span class="p"><strong>自主組成不同隊形</strong></span></h2>
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<div class="ace-line ace-line old-record-id-doxcnYKkqwmsm8AUISiXaHsWplf" style="text-align: justify;"><span class="p">系統(tǒng)會控制微型機械人轉(zhuǎn)換不同集群形態(tài),以便在不規(guī)則的環(huán)境中游走。</span></div>
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<div class="ace-line ace-line old-record-id-doxcnmgAgGwSwkUWCYBJheoVezb" style="text-align: justify;"><span class="p">微型機械人由磁性納米粒子組成,直徑只有400納米,相等于約千分之五條頭發(fā)直徑的尺度。 系統(tǒng)可以利用指定磁場引導(dǎo)一大群機械人轉(zhuǎn)換成三種不同的集群形態(tài),包括擴散群(spreading swarm,SS)、帶狀群(ribbon-like swarm,RS)及渦狀群(vortex-like swarm,VS),以執(zhí)行不同任務(wù),包括于目標位置進行靶向治療、藥物輸送等。 團隊期望這種結(jié)合人工智能的導(dǎo)航技術(shù),日后能應(yīng)用于治療大腦缺血性中風等血管性系統(tǒng)疾病,并且比現(xiàn)有標靶藥更精準地運送藥物到癌細胞。</span></div>
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<div class="ace-line ace-line old-record-id-doxcn6cQckgMCEiYeSOCnUOSgEc" style="text-align: justify;"><span class="h6">中大機械與自動化工程學系張立教授(中)的研究小組與中大計算機科學與工程學系竇琪教授(右二)合作。</span></div>
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<div class="ace-line ace-line old-record-id-doxcne8Gy2aicYaAe45wMn4gqMg" style="text-align: justify;"><span class="p">研究結(jié)果已刊登于國際學術(shù)期刊《Nature Machine Intelligence》,全文請參閱:<a href="https://www.nature.com/articles/s42256-022-00482-8" target="_blank" rel="noopener">https://www.nature.com/articles/s42256-022-00482-8</a>。</span></div>
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