Robin Murphy, uma roboticista da Texas A&M University, publicou um artigo da Focus na revista Science Robotics descrevendo suas opiniaµes sobre os robôs retratados em “Star Warsâ€, mais particularmente aqueles apresentados em “The Mandalorianï¿
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)
Pixabay
Robin Murphy, uma roboticista da Texas A&M University, publicou um artigo da Focus na revista Science Robotics descrevendo suas opiniaµes sobre os robôs retratados em “Star Warsâ€, mais particularmente aqueles apresentados em “The Mandalorian†e “The Book of Boba Fettâ€. Em seu artigo, ela diz acreditar que os retratos de robôs em ambos os filmes são bastante criativos, mas sugere que eles não são selvagens o suficiente para competir com robôs que são feitos e usados ​​no mundo real hoje.
Murphy comea§a observando que um roba´ em particular, o IG-11 no Mandaloriano, permite uma boa visualização com uma cabea§a rotativa que permite atirar em alvos em qualquer direção, mas ela também observa que esse roba´ provavelmente seria excessivamente suscetavel a falha conjunta e seria sobrecarregado com enormes demandas computacionais. Ela sugere que um projeto mais prático envolveria o uso de sensores de matriz fixa.
Murphy também observa que os robôs em filmes de "Guerra nas Estrelas" falham de vez em quando, geralmente durante cenas de suspense, o que ela observa ainda pode explicar por que o impanãrio encontrou seu fim. Como apenas um exemplo, ela se pergunta por que os stormtroopers costumam errar seus alvos. Ela também observa que, de certa forma, os droides nos filmes de "Guerra nas Estrelas" tendem a ser muito mais avana§ados do que os droides no mundo real, permitindo que eles tenham trabalhos semelhantes aos humanos, como bartender, ensinar ou traduzir. Ao fazer isso, ela aponta, os produtores dos filmes evitaram mostra¡-los fazendo trabalhos mais mundanos, como mineração.
No mundo real, ela ressalta, os robôs estãocada vez mais preenchendo papanãis laboriosos tradicionalmente desempenhados por humanos. Automatizar a mineração no mundo real, ela observa, levou a uma grande queda nos custos de ma£o de obra humana nos últimos 20 anos. Ela também se pergunta por que os drones são tão raramente apresentados em filmes de "Guerra nas Estrelas", observando que no mundo real , eles se tornaram uma parte importante dos esforços de guerra. Ela observa que em um esfora§o espacial real, um drone estãoatualmente ajudando um rover em Marte a evitar trechos de solo onde ele pode ficar preso.
Murphy conclui que uma das coisas que os filmes acertam éa alegria que os roboticistas podem trazer para aqueles que se beneficiam do design e da criação de robôs imaginativos em tantas áreas da vida.