9

These concepts are similar in the sense that they require multiple robots that communicate/cooperate. Apart from that, their application, and thus their design and implementation differ. Swarm Robots Swarm robots are designed after ants, bees and such creatures. The idea therefore is not just about multiple robots cooperating, but it's about many robots, ...


5

Let's say your environment is a weighted graph. The weight of each edge shows the distance. Edges ($E$) could be roads and nodes ($V$) could be junctions. Let's further assume that each robot has velocity $v$. You say each "point" needs to be surveyed every $h$ hours. I assume that means each point in the city, which means each point in every road and ...


5

How close together? If they use the same make and model GPS unit, you MIGHT be able to use the relative positions calculated via GPS. A lot of the sources of GPS error would be the same for both vehicles in that case (e.g., atmospherics, any built-in GPS filtering). Each vehicle could broadcast it's state vector to the other one.


4

The company is called Flashhold, here is the link to the website: http://www.flashhold.com/ They raised more than 29M$ in aseries B funding recently and seem to gain a lot of traction https://www.chinamoneynetwork.com/2017/03/30/cainiao-softbank-lead-29m-round-in-chinese-logistic-robot-firm-flashhold Hope this helps, do not hesitate to exchange back if you ...


4

It is possible that two independent GPS units might be accurate enough (as ViennaMike suggests) if both are sufficiently similar, get a lock from the same location, follow roughly the same paths (so the accumulated differential GPS errors are roughly the same) and are re-synchronised at regular intervals. This might be significantly assisted though if you ...


3

The kalman filter that you've already been using on single robots can be broadened to apply to the swarm of robots. If you previously represented the state of a single robot with 5 variables, and you have 3 robots, then combine all 3 robot states into one state with 15 variables. That larger state representing the entire group could reasonably be called the "...


3

You can do it by fusion using a Kalman filter: You have a process model model: $$ x_t = g(x_{t-1},u_t) $$ Now, you have multiple measurements of the same process model from different perspectives: $$ z1_t = h_1(x_{t}) \leftarrow \text{camera 1} \\ z2_t = h_2(x_{t}) \leftarrow \text{camera 2} \\ \cdots \\ zn_t = h_n(x_{t}) \leftarrow \text{camera n} \\ $$ ...


3

A standard way to model that kind of discrete-event behavior is through Petri Nets or a Parallel Composition of Automata. An interesting start might be to simply create the model and see if it works in simulation first. That will help you solve the high-level logic of your problem. After that is dealt with, you can begin to think about which robot you want ...


3

The generic answer is yes, such a project could be implemented using existing hardware and frameworks (ROS, MRDS, something else, or none). The collaboration part is pretty simple in this scenario, it's a straightforward handshake between producer & consumer. The hard part would be first defining each of the jobs in detail, procuring hardware that ...


3

How close together is important. I saw the range of 0-5m, but if you're suggesting that they might touch, or just barely not touch, then you're going to have difficulties. Lightweight is also a vague term which will need to be defined better in order to adequately answer your question. Still, there are some things to keep in mind: Augmented GPS can get you ...


2

6-DOF is kind of difficult.. You could do vision but that is hard to implement robustly. You say the UAVs are localizing themselves using GPS; are you using an IMU+Kalman filtering as well? For proximity detection you could try infrared/ultrasonic sensors, e.g. https://www.sparkfun.com/products/242. You could combine this with the Kalman filter to get a ...


2

Depending on how much you wanted to play with the GPS signals, you could use some form of differential GPS to calculate their relative positions way more precisely than using the WGS84 outputs would give you. Basically this would remove most of the inaccuracies coming from atmospheric effects and ephemeris errors. The exact precision would depend on the ...


2

You could have a look at the papers of the kilobot project. They have your capabilities so it would be a good starting point.


2

In addition to @Shahbaz According to this book Multiple Mobile Robot Systems is main topic and swarm robotics is a sub topic both of them motivated from the task complexity is too high for a single robot to accomplish the task is inherently distributed building several resource-bounded robots is much easier than having a single powerful robot multiple ...


2

I came across one paper that had a good description of this issue from Kristina Lerman and Aram Galstyan at University of Southern California entitled "Mathematical Model of Foraging in a Group of Robots: Effect of Interference"


2

In general - robots refer to real or simulated mechanical systems, whereas an agent could be a physical or non-physical entity like a chatbot program or neural net.


1

First, it's important to note that depending on your problem specifications, we may not know of any good algorithms to solve it - this is especially true when you start to add in more problem constraints. There are three levels of abstraction here - your question primarily deals with the highest level, but FLYAQ covers all three so I include them here as ...


1

It sounds like a KD-tree If it is a KD-tree, the four floats seem a little redundant, bounding boxes can be calculated on the fly when traversing the tree, you only need to record the splitting plane in the node. I would guess that begin and end describe range of indices of agents belonging to the current node and left and right are indices of left and ...


1

It appears that Nikolaus Correll at CU-Boulder is doing research with a derivative of the kilobots: http://www.colorado.edu/news/releases/2012/12/14/cu-boulder-team-develops-swarm-pingpong-ball-sized-robots


1

You could use the gps system for long-range co-ordination, an altimeter for height, and ultra-sonic sensors for close-range co-ordination. When the planes get in to close proximity the ultrasonic sensors would work for collision prevention. The only extra weight would be ultrasonic sensors, and an altimeter.


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