对于在隧道等狭窄空间中运行的蚂蚁和机器人，拥有更多的工人并不一定意味着要完成更多的工作。正如厨房里太多的厨师以彼此的方式得到的一样，在隧道中拥有太多机器人也会产生堵塞，可以使工作陷入困境。
8月17日发表的一项研究Science表明，在消防蚂蚁殖民地中，少数工人在挖掘大部分工作，而其他蚂蚁看起来比勤劳少了。为了挖掘巢穴隧道，这种不那么忙碌的方法在没有蚂蚁交通拥堵的情况下完成了工作 - 确保平滑的挖掘流程。研究人员发现，将蚂蚁优化策略应用于自主机器人会避免机械化的堵塞，并以最少的能量完成工作。
Optimizing the activity of autonomous underground robots could be useful for tasks such as disaster recovery, mining or even digging underground shelters for future planetary explorers. The research was supported by the National Science Foundation’s Physics of Living Systems program, the Army Research Office and the Dunn Family Professorship.
“We noticed that if you have 150 ants in a container, only 10 or 15 of them will actually be digging in the tunnels at any given time,” said Daniel Goldman, a professor in the School of Physics at the Georgia Institute of Technology. “We wanted to know why, and to understand how basic laws of physics might be at work. We found a functional, community benefit to this seeming inequality in the work environment. Without it, digging just doesn’t get done.”
通过监视绘制的30只蚂蚁的活动，以识别每个人，高盛和同事，包括前博士后同胞达里亚·莫纳科娃（Daria Monaenkova）和博士学位。学生巴尼西卡·杜塔（Bahnisikha Dutta）发现，只有30％的蚂蚁正在做70％的工作 - 这种不平等似乎使工作保持不变。但是，这显然不是因为最繁忙的蚂蚁是最合格的。当研究人员从巢容器中取出五个最努力的蚂蚁时，随着其余25人继续挖掘，他们没有发现生产力下降。
拥有巢穴对于火蚂蚁至关重要，例如，如果殖民地被洪水流离失所，例如，蚂蚁到达干燥土地时所做的第一件事就是开始挖掘。他们的隧道狭窄，几乎足够宽，可以通过两个蚂蚁通过，这是一种设计特征，假设在发育中的垂直隧道中具有运动优势。尽管如此，蚂蚁还是知道如何通过从其他工人占领的隧道中撤退来避免制造堵塞，有时甚至没有做任何事情。
To avoid clogs and maximize digging in the absence of a leader, robots built by Goldman’s master’s degree student Vadim Linevich were programmed to capture aspects of the dawdling and retreating ants. The researchers found that as many as three robots could work effectively in a narrow horizontal tunnel digging 3D printed magnetic plastic balls that simulated sticky soil. If a fourth robot entered the tunnel, however, that produced a clog that stopped the work entirely.
“When we put four robots into a confined environment and tried to get them to dig, they immediately jammed up,” said Goldman, who is the Dunn Family Professor in the School of Physics. “While observing the ants, we were surprised to see that individuals would sometimes go to the tunnel and if they encountered even a small amount of clog, they’d just turn around and retreat. When we put those rules into combinations with the robots, that created a good strategy for digging rapidly with low amounts of energy use per robot.”
Experimentally, the research team tested three potential behaviors for the robots, which they termed “eager,” “reversal” or “lazy.” Using the eager strategy, all four robots plunged into the work — and quickly jammed up. In the reversal behavior, robots gave up and turned around when they encountered delays reaching the work site. In the lazy strategy, dawdling was encouraged.
高盛说：“如果您只有三个机器人，急切的策略是最好的策略，但是如果您添加第四个机器人，那是因为它们以彼此的方式获得的行为坦克。”“逆转产生相对理智和明智的挖掘。这不是最快的策略，但没有果酱。如果您看消耗的能量，那么懒惰是最好的路线。”由以前的博士领导的基于玻璃状和过冷流体的分析技术。学生杰弗里·阿吉拉尔（Jeffrey Aguilar）深入了解了如何缓解和防止堵塞簇的不同策略。
To understand what was going on and experiment with the parameters, Goldman and colleagues — including Will Savoie, a Georgia Tech Ph.D. student, Research Assistant Hui-Shun Kuan and Professor Meredith Betterton from the School of Physics at University of Colorado at Boulder — used computer modeling known as cellular automata that has similarities to the way in which traffic engineers model the movement of cars and trucks on a highway.
“On highways, too few cars don’t provide much flow, while too many cars create a jam,” Goldman said. “There is an intermediate level where things are best, and that is called the fundamental diagram. From our modeling, we learned that the ants are working right at the peak of the diagram. The right mix of unequal work distributions and reversal behaviors has the benefit of keeping them moving at maximum efficiency without jamming.”
研究人员使用了为研究设计和建造的机器人，但它们与蚂蚁的能力不匹配。蚂蚁柔软而坚固，能够在范围内互相挤压，这会导致僵化的机器人堵塞。在某些情况下，高盛实验室中的机器人甚至互相损坏，同时徘徊在挖掘位置。
The research findings could be useful for space exploration where tunnels might be needed to quickly shield humans from approaching dust storms or other threats. “If you were a robot swarm on Mars and needed to dig deeply in a hurry to get away from dust storms, this strategy might help provide shelter without having perfect information about what everybody was doing,” Goldman explained.
Beyond the potential robotics applications, the work provides insights into the complex social skills of ants and adds to the understanding of active matter.
“Ants that live in complex subterranean environments have to develop sophisticated social rules to avoid the bad things that can happen when you have a lot of individuals in a crowded environment,” Goldman said. “We are also contributing to understanding the physics of task-oriented active matter, putting more experimental knowledge into phenomenon such as swarms.”
Filed Under:Industrial automation,Robotics • robotic grippers • end effectors
