Time-sensitive applications, such as search and rescue missions, smart factories, and smart city intersections, are increasingly using collaborative multi-agent systems. Traditional communications networks are not designed for large-scale multi-agent systems that require time-sensitive information exchange to communicate efficiently. WiFi is a popular alternative for deploying time-sensitive applications because it is cheap, reliable, and widely available in sensors, cameras, and other sensors.

When many robots transmit time-sensitive data over a wireless network, a data traffic jam can occur, making it difficult to provide a useful, real-time report. New data is critical for drones searching for survivors in a disaster area or robots checking a building.

Engineers at MIT have developed a method to tailor any wireless network to handle a large amount of time-sensitive data from a variety of sources. Their new strategy, WiSwarm, configures a wireless network to monitor the flow of information from many sources and ensure that the network is relaying the most up-to-date data.

The method developed by the team enables many robots to communicate over Wi-Fi networks without the need for expensive communication and processing hardware.

Vishrant Tripathi from MIT said: “What happens in most standard network protocols is a first come, first served approach. A video frame comes in and you process it. Another comes in, you process it. But if your task is time-sensitive, such as trying to detect where a moving object is, then all old video frames are useless. What you want is the latest video frame.

Modiano explains, “Age-of-information is a new measure of information freshness that considers latency from an application perspective.”

The team developed WiSwarm for prioritizing information about aging. This scheduling algorithm can be run on a centralized computer and linked to any wireless network to manage many data streams and prioritize the most recent data.

The team used their method to modify a conventional Wi-Fi router, demonstrating that the custom-built network could act as an efficient traffic cop, prioritizing and relaying the latest data to multiple drones for keeping vehicle tracking working.

The algorithm determines which source on a network should send data next, using a “last in, first out” protocol to send the most recent data over the wireless network to a central processor.

WiSwarm determines which source on a network to send data next by weighing three factors: the general weight of a drone, priority (for example, a drone tracking a fast vehicle may need to be updated more frequently and thus has a higher priority than a drone following a slower vehicle) vehicle); the information age of a drone, or how long it has been since a drone has sent an update; and a drone’s channel fidelity, or the likelihood of successfully transmitting data.

By multiplying these three parameters for each drone at a given time, the algorithm can schedule drones to report updates one by one over a wireless network without clogging the system.

The team tested their algorithm with multiple mobility-tracking drones. The researchers equipped flying drones with a small camera and a simple computer chip with Wi-Fi, which they used to continuously transmit images to a central computer.

Linking the network to their algorithm allowed the computer to receive the latest images from the most relevant drones, which it then used to send commands back to the drones to keep them on the vehicle’s trail.

When the researchers tested the system with two drones, they found it could transmit data that was twice as fresh, resulting in six times better tracking. When the system expanded to five drones and five ground vehicles, Wi-Fi alone could not handle the increased data traffic and the drones quickly lost track of the ground vehicles. WiSwarm improved the network’s capabilities, allowing all drones to continue tracking their cars.

Tal said, “Our work is the first work to show that Information Age can work for real robot applications.”

Karaman said, “Imagine self-driving cars arriving at an intersection with a sensor that sees something around the corner. Which car should get that data first? It is a problem where timing and freshness of data matter.”

In the near future, low-cost and agile drones could collaborate and communicate over wireless networks to survey buildings, agricultural fields, and wind and solar farms. The concept could be critical to controlling data streaming in smart cities.

The result shows that WiSwarm offers much better tracking than Wi-Fi with only two UAVs.

Magazine reference:

  1. Vishrant Tripathi, Igor Kadota, et al. WiSwarm: Information-enabled wireless networking for UAV collaborative teams. arXiv DOI: 10.48550/arXiv.2212.03298