Swarm robotics

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Swarm of open-source Jasmine micro-robots recharging themselves RechargingSwarm.jpg
Swarm of open-source Jasmine micro-robots recharging themselves
A team of iRobot Create robots at the Georgia Institute of Technology IRobot Create team.jpg
A team of iRobot Create robots at the Georgia Institute of Technology

Swarm robotics is the study of how to design independent systems of robots without centralized control. The emerging swarming behavior of robotic swarms is created through the interactions between individual robots and the environment. [1] This idea emerged on the field of artificial swarm intelligence, as well as the studies of insects, ants and other fields in nature, where swarm behavior occurs. [2]

Contents

Relatively simple individual rules can produce a large set of complex swarm behaviors. A key component is the communication between the members of the group that build a system of constant feedback. The swarm behavior involves constant change of individuals in cooperation with others, as well as the behavior of the whole group.

Key Attributes of Robotic Swarms

The design of swarm robotics systems is guided by swarm intelligence principles, which promote fault tolerance, scalability, and flexibility. [1] Unlike distributed robotic systems in general, swarm robotics emphasizes a large number of robots. While various formulations of swarm intelligence principles exist, one widely recognized set includes:

  1. Robots are autonomous.
  2. Robots can interact with the surroundings and give feedback to modify the environment.
  3. Robots possess local perceiving and communicating capabilities, such as wireless transmission systems, like radio frequency or infrared. [3]
  4. Robots do not exploit centralized swarm control or global knowledge.
  5. Robots cooperate with each other to accomplish the given task. [4]

Miniaturization is also key factor in swarm robotics, as the effect of thousands of small robots can maximize the effect of the swarm-intelligent approach to achieve meaningful behavior at swarm-level through a greater number of interactions on an individual level. [5]

Compared with individual robots, a swarm can commonly decompose its given missions to their subtasks; [6] a swarm is more robust to partial failure and is more flexible with regard to different missions. [7]

History

The phrase "swarm robotics" was reported to make its first appearance in 1991 according to Google Scholar, but research regarding swarm robotics began to grow in early 2000s. The initial goal of studying swarm robotics was to test whether the concept of stigmergy could be used as a method for robots to indirectly communication and coordinate with each other. [5]

One of the first international projects regarding swarm robotics was the SWARM-BOTS project funded by the European Commission between 2001 and 2005, in which a swarm of up to 20 of robots capable of independently physically connect to each other to form a cooperating system were used to study swarm behaviors such as collective transport, area coverage, and searching for objects. The result was demonstration of self-organized teams of robots that cooperate to solve a complex task, with the robots in the swarm taking different roles over time. This work was then expanded upon through the Swarmanoid project (2006–2010), which extended the ideas and algorithms developed in Swarm-bots to heterogeneous robot swarms composed of three types of robots—flying, climbing, and ground-based—that collaborated to carry out a search and retrieval task. [5]

Applications

There are many potential applications for swarm robotics. [8] They include tasks that demand miniaturization (nanorobotics, microbotics), like distributed sensing tasks in micromachinery or the human body. A promising use of swarm robotics is in search and rescue missions. [9] Swarms of robots of different sizes could be sent to places that rescue-workers cannot reach safely, to explore the unknown environment and solve complex mazes via onboard sensors. [9] Swarm robotics can also be suited to tasks that demand cheap designs, for instance mining or agricultural shepherding tasks. [10]

Drone swarms

A 100 drone swarm flight commemorating the 100th anniversary of the Korea Aerospace Research Institute 3 1jeol 100junyeon ginyeom 100dae deuron gunjibbihaeng (4) (1155).png
A 100 drone swarm flight commemorating the 100th anniversary of the Korea Aerospace Research Institute

Drone swarms are used in target search, drone displays, and delivery. A drone display commonly uses multiple, lighted drones at night for an artistic display or advertising. A delivery drone swarm can carry multiple packages to a single destination at a time and overcome a single drone's payload and battery limitations. [11] A drone swarm may undertake different flight formations to reduce overall energy consumption due to drag forces. [12]

Drone swarming can also introduce additional control issues connected to human factors and the swarm operator. Examples of this include high cognitive demand and complexity when interacting with multiple drones due to changing attention between different individual drones. [13] [14] Communication between operator and swarm is also a central aspect. [15]

Military swarms

More controversially, swarms of military robots can form an autonomous army. U.S. Naval forces have tested a swarm of autonomous boats that can steer and take offensive actions by themselves. The boats are unmanned and can be fitted with any kind of kit to deter and destroy enemy vessels. [16]

During the Syrian Civil War, Russian forces in the region reported attacks on their main air force base in the country by swarms of fixed-wing drones loaded with explosives. [17]

Miniature swarms

Another large set of applications may be solved using swarms of micro air vehicles, which are also broadly investigated nowadays. In comparison with the pioneering studies of swarms of flying robots using precise motion capture systems in laboratory conditions, [18] current systems such as Shooting Star can control teams of hundreds of micro aerial vehicles in outdoor environment [19] using GNSS systems (such as GPS) or even stabilize them using onboard localization systems [20] where GPS is unavailable. [21] [22] Swarms of micro aerial vehicles have been already tested in tasks of autonomous surveillance, [23] plume tracking, [24] and reconnaissance in a compact phalanx. [25] Numerous works on cooperative swarms of unmanned ground and aerial vehicles have been conducted with target applications of cooperative environment monitoring, [26] simultaneous localization and mapping, [27] convoy protection, [28] and moving target localization and tracking. [29]

Acoustic swarms

In 2023, University of Washington and Microsoft researchers demonstrated acoustic swarms of tiny robots that create shape-changing smart speakers. [30] These can be used for manipulating acoustic scenes to focus on or mute sounds from a specific region in a room. [31] Here, tiny robots cooperate with each other using sound signals, without any cameras, to navigate cooperatively with centimeter-level accuracy. These swarm devices spread out across a surface to create a distributed and reconfigurable wireless microphone array. They also navigate back to the charging station where they can be automatically recharged. [32]

Kilobot

Most efforts have focused on relatively small groups of machines. However, a Kilobot swarm consisting of 1,024 individual robots was demonstrated by Harvard in 2014, the largest to date. [33]

LIBOT

Another example of miniaturization is the LIBOT Robotic System [34] that involves a low cost robot built for outdoor swarm robotics. The robots are also made with provisions for indoor use via Wi-Fi, since the GPS sensors provide poor communication inside buildings.

A swarm of open source micro Colias robots Swarm of Colias Robot.jpg
A swarm of open source micro Colias robots

Colias

Another such attempt is the micro robot (Colias), [35] built in the Computer Intelligence Lab at the University of Lincoln, UK. This micro robot is built on a 4 cm circular chassis and is a low-cost and open platform for use in a variety of swarm robotics applications.

Manufacturing swarms

Additionally, progress has been made in the application of autonomous swarms in the field of manufacturing, known as swarm 3D printing. This is particularly useful for the production of large structures and components, where traditional 3D printing is not able to be utilized due to hardware size constraints. Miniaturization and mass mobilization allows the manufacturing system to achieve scale invariance, not limited in effective build volume. While in its early stage of development, swarm 3D printing is currently being commercialized by startup companies. [36]

See also

Related Research Articles

An autonomous robot is a robot that acts without recourse to human control. Historic examples include space probes. Modern examples include self-driving vacuums and cars.

<span class="mw-page-title-main">Unmanned aerial vehicle</span> Aircraft without any human pilot on board

An unmanned aerial vehicle (UAV), or unmanned aircraft system (UAS), commonly known as a drone, is an aircraft with no human pilot, crew, or passengers on board. UAVs were originally developed through the twentieth century for military missions too "dull, dirty or dangerous" for humans, and by the twenty-first, they had become essential assets to most militaries. As control technologies improved and costs fell, their use expanded to many non-military applications. These include aerial photography, area coverage, precision agriculture, forest fire monitoring, river monitoring, environmental monitoring, policing and surveillance, infrastructure inspections, smuggling, product deliveries, entertainment, and drone racing.

Robotic control is the system that contributes to the movement of robots. This involves the mechanical aspects and programmable systems that makes it possible to control robots. Robotics can be controlled by various means including manual, wireless, semi-autonomous, and fully autonomous.

<span class="mw-page-title-main">Swarm behaviour</span> Collective behaviour of a large number of (usually) self-propelled entities of similar size

Swarm behaviour, or swarming, is a collective behaviour exhibited by entities, particularly animals, of similar size which aggregate together, perhaps milling about the same spot or perhaps moving en masse or migrating in some direction. It is a highly interdisciplinary topic.

<span class="mw-page-title-main">Military robot</span> Robotic devices designed for military applications

Military robots are autonomous robots or remote-controlled mobile robots designed for military applications, from transport to search & rescue and attack.

<span class="mw-page-title-main">Boids</span> Artificial life program

Boids is an artificial life program, developed by Craig Reynolds in 1986, which simulates the flocking behaviour of birds, and related group motion. His paper on this topic was published in 1987 in the proceedings of the ACM SIGGRAPH conference. The name "boid" corresponds to a shortened version of "bird-oid object", which refers to a bird-like object. Reynolds' boid model is one example of a larger general concept, for which many other variations have been developed since. The closely related work of Ichiro Aoki is noteworthy because it was published in 1982 — five years before Reynolds' boids paper.

<span class="mw-page-title-main">Micro air vehicle</span> Class of very small unmanned aerial vehicle

A micro air vehicle (MAV), or micro aerial vehicle, is a class of man-portable miniature UAVs whose size enables them to be used in low-altitude, close-in support operations. Modern MAVs can be as small as 5 centimeters - compare Nano Air Vehicle. Development is driven by commercial, research, government, and military organizations; with insect-sized aircraft reportedly expected in the future. The small craft allow remote observation of hazardous environments or of areas inaccessible to ground vehicles. Hobbyists have designed MAVs for applications such as aerial robotics contests and aerial photography. MAVs can offer autonomous modes of flight.

<span class="mw-page-title-main">Dario Floreano</span> Swiss-Italian roboticist and engineer

Dario Floreano is a Swiss-Italian roboticist and engineer. He is Director of the Laboratory of Intelligent System (LIS) at the École Polytechnique Fédérale de Lausanne in Switzerland and was the founding director of the Swiss National Centre of Competence in Research (NCCR) Robotics.

<span class="mw-page-title-main">Unmanned ground vehicle</span> Type of vehicle

An unmanned ground vehicle (UGV) is a vehicle that operates while in contact with the ground without an onboard human presence. UGVs can be used for many applications where it is inconvenient, dangerous, expensive, or impossible to use an onboard human operator. Typically, the vehicle has sensors to observe the environment, and autonomously controls its behavior or uses a remote human operator to control the vehicle via teleoperation.

<span class="mw-page-title-main">Mobile robot</span> Type of robot

A mobile robot is an automatic machine that is capable of locomotion. Mobile robotics is usually considered to be a subfield of robotics and information engineering.

Physicomimetics is physics-based swarm (computational) intelligence. The word is derived from physike and mimesis.

The Guidance, Control and Decision Systems Laboratory (GCDSL) is situated in the Department of Aerospace Engineering at the Indian Institute of Science in Bangalore, India. The Mobile Robotics Laboratory (MRL) is its experimental division. They are headed by Dr. Debasish Ghose, Full Professor.

<span class="mw-page-title-main">Uncrewed vehicle</span> Type of vehicle

An uncrewed vehicle or unmanned vehicle is a vehicle without a person on board. Uncrewed vehicles can either be under telerobotic control—remote controlled or remote guided vehicles—or they can be autonomously controlled—autonomous vehicles—which are capable of sensing their environment and navigating on their own.

Ant robotics is a special case of swarm robotics. Swarm robots are simple robots with limited sensing and computational capabilities. This makes it feasible to deploy teams of swarm robots and take advantage of the resulting fault tolerance and parallelism. Swarm robots cannot use conventional planning methods due to their limited sensing and computational capabilities. Thus, their behavior is often driven by local interactions. Ant robots are swarm robots that can communicate via markings, similar to ants that lay and follow pheromone trails. Some ant robots use long-lasting trails. Others use short-lasting trails including heat and alcohol. Others even use virtual trails.

An autonomous aircraft is an aircraft which flies under the control of on-board autonomous robotic systems and needs no intervention from a human pilot or remote control. Most contemporary autonomous aircraft are unmanned aerial vehicles (drones) with pre-programmed algorithms to perform designated tasks, but advancements in artificial intelligence technologies mean that autonomous control systems are reaching a point where several air taxis and associated regulatory regimes are being developed.

Swarm robotic platforms apply swarm robotics in multi-robot collaboration. They take inspiration from nature. The main goal is to control a large number of robots to accomplish a common task/problem. Hardware limitation and cost of robot platforms limit current research in swarm robotics to mostly performed by simulation software. On the other hand, simulation of swarm scenarios that needs large numbers of agents is extremely complex and often inaccurate due to poor modelling of external conditions and limitation of computation.

Swarm 3D printing or cooperative 3D printing or swarm manufacturing is a digital manufacturing platform that employs a swarm of mobile robots with different functionalities to work together to print and assemble products based on digital designs. A digital design is first divided into smaller chunks and components based on its geometry and functions, which are then assigned to different specialized robots for printing and assembly in parallel and in sequence based on the dependency of the tasks. The robots typically move freely on an open factory floor, or through the air, and could carry different tool heads. Some common tool heads include material deposition tool heads, pick and place tool head for embedding of pre-manufactured components, laser cutter, welding tool, etc. In some cases, operations are managed by artificial intelligence algorithms, increasingly prevalent with larger swarms or more complex robots, which require elements of autonomy to work together effectively. While in its early stage of development, swarm 3D printing is currently being commercialized by startup companies. According to Additive Manufacturing Magazine, AMBOTS is credited with creating the first end-to-end solution for cooperative 3D printing. Using the Rapid Induction Printing metal additive manufacturing process, Rosotics was the first company to demonstrate swarm 3D printing using a metallic payload, and the only to achieve metallic 3D printing from an airborne platform.

<span class="mw-page-title-main">Drones in wildfire management</span> Use of drones/UAS/UAV in wildfire suppression and management

Drones, also known as Unmanned Aerial Systems/Vehicles (UAS/UAV), or Remotely Piloted Aircraft, are used in wildfire surveillance and suppression. They help in the detection, containment, and extinguishing of fires. They are also used for locating a hot spot, firebreak breaches, and then to deliver water to the affected site. In terms of maneuverability, these are superior to a helicopter or other forms of manned aircraft. They help firefighters determine where a fire will spread through tracking and mapping fire patterns. These empower scientists and incident personnel to make informed decisions. These devices can fly when and where manned aircraft are unable to fly. They are associated with low cost and are flexible devices that offer a high spatiotemporal resolution.

<span class="mw-page-title-main">Margarita Chli</span> Greek computer vision and robotics researcher

Margarita Chli is an assistant professor and leader of the Vision for Robotics Lab at ETH Zürich in Switzerland. Chli is a leader in the field of computer vision and robotics and was on the team of researchers to develop the first fully autonomous helicopter with onboard localization and mapping. Chli is also the Vice Director of the Institute of Robotics and Intelligent Systems and an Honorary Fellow of the University of Edinburgh in the United Kingdom. Her research currently focuses on developing visual perception and intelligence in flying autonomous robotic systems.

References

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