An insectoid robot is a, usually small, robot featuring some insect-like features. These can include the methods of locomotion (including flying), methods of navigation, and artificial intelligence based on insect models. Many of the problems faced by miniature robot designers have been solved by insect evolution. Researchers naturally look to insects for inspiration and solutions.
Robot locomotion has frequently been inspired by insect physiology. These robots typically take the form of a hexapod. Research has become multidisciplinary, involving not only robotics engineers, but also biologists, especially neurobiologists. Engineers gain from thisrelationship by acquiring a better understanding of the functioning of the insects they have used to model their robots. Biologists in turn, gain a platform on which they can test their theories of insect motor control. [1]
Building a robot that can walk on a flat surface in the laboratory is a fairly straightforward task. A hexapod robot with mechanically linked simple pegs for legs will achieve this task. Then again, a wheeled robot might be even simpler, but may be entirely unable to solve the much more difficult problem of crossing rough terrain with unpredictable obstacles. For this, articulated joints in legs like a real insect, with sensor-motor control like the neurology of a real insect are needed. A simple rhythmic cycle of the legs will not do. The legs and joints must be controlled individually and in combination according to information received from limb position and load sensors. [2]
The gait of insects changes with desired speed. Research has shown that these gait patterns can still be generated locally in many insects even when completely disconnected from the central nervous system. [3] In some insects, for instance the cockroach, the gait changes in a running insect partly because the nervous system of the insect cannot respond rapidly enough. A running cockcroach changes its gait to pushing with all three legs on one side together. The characteristic side-to-side motion of the animal is at the biomechanical resonant frequency set by the insect's weight and spring stiffness of the combined legs. This mode needs no input from an external controller and it is both efficient and stable. [4] Researchers recognise the advantages of features of real insects, but as of 2004, "they have only rarely come together in a robot..." [5]
For a very small aircraft, fixed-wing flight becomes impractical due to rapidly decreasing lift-to-drag ratio with size. Insect flight, on the other hand, is always ornithopteric which suggests an approach for insectoid robots. Ma et al. for instance, developed a tethered robot fly with flapping wings constructed of piezoelectric material. Ma chose to model the robot on the fly because, according to their paper, it is the most agile creature alive, and therefore the most difficult to emulate as a robot. [6]
Insects have very little resource to devote to intelligence in the human sense of brain processing power. The number of neurons in an insect varies by species from one million to as few as ten thousand. [7] By comparison, humans have 86 billion neurons. [8] Further, large brains are extremely energy hungry. Insects must therefore find other methods of developing intelligence such as embodying intelligence in hardware, local sensor-motor connections, and swarm intelligence. At one time it was hoped that robots would avoid the need for such solutions because of the rapidly increasing processing power and decreasing size of computers according to Moore's law. However, this process seems to be reaching its limit and insect solutions look increasingly attractive. [9]
Walking rhythms independent of the central nervous system in cockroaches have already been mentioned. A major breakthrough in flying insectoid robots came by applying the same principles to the wings. Attempts to control the angle of attack of the wings with a central processor were not successful because a lift to weight ratio greater than unity could not be achieved. Removing the processor and allowing the wings to rotate passively at the natural frequency of the mechanical system reduced the weight sufficiently to allow controlled insectoid flight for the first time [10] in 2008 with a fly-like robot. However, the robot was externally powered through an umbilical rather than completely free flight. [11]
Swarms of robots can solve problems that are not possible to solve with the limited processing resource of a single robot. They are particular useful in exploration tasks. They can be used to find the shortest route to a destination, and have been proposed to search for gas sources in dangerous environments. Another proposal is robots that self-assemble into a structure to allow the swarm to cross a gap in the manner of ants. [12]
Flying insects have poor visual spatial resolution, must respond rapidly, and have little to no advanced neural processing power. Due to limitations of space and weight, flying insectoid robots have a very similar set of problems. In 2003, Franceschini et al. investigated the possibility of using insect solutions to solve robot navigation problems. Franceschini built a research robot based on the neural physiology of a fly. The robot was not actually a flying robot, rather, it was a wheeled vehicle. [13] The aim of the research was to show that simple sensor-motor control using only visual motion detection could navigate a course. [14]
Using insect intelligence in robot navigation has been going on since 1986, but initially was not taken up by engineers building robots. It was felt that because insects lack a visual cortex, and hence cannot perform advanced visual processing and image formation, a robot based on such technology would not be very successful. Franceschini argues that it is not necessary to possess a visual cortex for the navigation task, and it would in fact be an unnecessary burden on an insect robot (both weight and processing time would be issues). Franceschini points out that many of the visual systems in humans do not pass through the visual cortex either. It is not always necessary to form images and identify objects. [15]
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.
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. Development is driven by commercial, research, government, and military purposes; with insect-sized aircraft reportedly expected in the future. The small craft allows remote observation of hazardous environments inaccessible to ground vehicles. MAVs have been built for hobby purposes such as aerial robotics contests and aerial photography.
A gait is a manner of limb movements made during locomotion. Human gaits are the various ways in which humans can move, either naturally or as a result of specialized training. Human gait is defined as bipedal forward propulsion of the center of gravity of the human body, in which there are sinuous movements of different segments of the body with little energy spent. Varied gaits are characterized by differences such as limb movement patterns, overall velocity, forces, kinetic and potential energy cycles, and changes in contact with the ground.
Swarm robotics is an approach to the coordination of multiple robots as a system which consist of large numbers of mostly simple physical robots. ″In a robot swarm, the collective behavior of the robots results from local interactions between the robots and between the robots and the environment in which they act.″ It is supposed that a desired collective behavior emerges from the interactions between the robots and interactions of robots with the environment. This approach emerged on the field of artificial swarm intelligence, as well as the biological studies of insects, ants and other fields in nature, where swarm behaviour occurs.
Robot locomotion is the collective name for the various methods that robots use to transport themselves from place to place.
Remote control animals are animals that are controlled remotely by humans. Some applications require electrodes to be implanted in the animal's nervous system connected to a receiver which is usually carried on the animal's back. The animals are controlled by the use of radio signals. The electrodes do not move the animal directly, as if controlling a robot; rather, they signal a direction or action desired by the human operator and then stimulate the animal's reward centres if the animal complies. These are sometimes called bio-robots or robo-animals. They can be considered to be cyborgs as they combine electronic devices with an organic life form and hence are sometimes also called cyborg-animals or cyborg-insects.
Campaniform sensilla are a class of mechanoreceptors found in insects, which respond to local stress and strain within the animal's cuticle. Campaniform sensilla function as proprioceptors that detect mechanical load as resistance to muscle contraction, similar to mammalian Golgi tendon organs. Sensory feedback from campaniform sensilla is integrated in the control of posture and locomotion.
A six-legged walking robot should not be confused with a Stewart platform, a kind of parallel manipulator used in robotics applications.
Legged robots are a type of mobile robot which use articulated limbs, such as leg mechanisms, to provide locomotion. They are more versatile than wheeled robots and can traverse many different terrains, though these advantages require increased complexity and power consumption. Legged robots often imitate legged animals, such as humans or insects, in an example of biomimicry.
Nouvelle artificial intelligence (AI) is an approach to artificial intelligence pioneered in the 1980s by Rodney Brooks, who was then part of MIT artificial intelligence laboratory. Nouvelle AI differs from classical AI by aiming to produce robots with intelligence levels similar to insects. Researchers believe that intelligence can emerge organically from simple behaviors as these intelligences interacted with the "real world," instead of using the constructed worlds which symbolic AIs typically needed to have programmed into them.
Robot localization denotes the robot's ability to establish its own position and orientation within the frame of reference. Path planning is effectively an extension of localisation, in that it requires the determination of the robot's current position and a position of a goal location, both within the same frame of reference or coordinates. Map building can be in the shape of a metric map or any notation describing locations in the robot frame of reference.
The Micromechanical Flying Insect (MFI) is a miniature UAV composed of a metal body, two wings, and a control system. Launched in 1998, it is currently being researched at University of California, Berkeley. The MFI is among a group of UAVs that vary in size and function. The MFI is proving to be a practical approach for specific situations. The US Office of Naval Research and Defense Advanced Research Project Agency are funding the project. The Pentagon hopes to use the robots as covert "flies on the wall" in military operations. Other prospective uses include space exploration and search and rescue.
Robotics is the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots. Robotics is related to the sciences of electronics, engineering, mechanics, and software.
Robotics is an interdisciplinary branch of electronics and communication, computer science and engineering. Robotics involves the design, construction, operation, and use of robots. The goal of robotics is to design machines that can help and assist humans. Robotics integrates fields of mechanical engineering, electrical engineering, information engineering, mechatronics engineering, electronics, biomedical engineering, computer engineering, control systems engineering, software engineering, mathematics, etc.
The following outline is provided as an overview of and topical guide to robotics:
A scolopidium is the fundamental unit of a mechanoreceptor organ in insects. It is a composition of three cells: a scolopale cap cell which caps the scolopale cell, and a bipolar sensory nerve cell.
RoboBee is a tiny robot capable of partially untethered flight, developed by a research robotics team at Harvard University. The culmination of twelve years of research, RoboBee solved two key technical challenges of micro-robotics. Engineers invented a process inspired by pop-up books that allowed them to build on a sub-millimeter scale precisely and efficiently. To achieve flight, they created artificial muscles capable of beating the wings 120 times per second.
The DelFly is a fully controllable camera-equipped flapping wing Micro Air Vehicle or Ornithopter developed at the Micro Air Vehicle Lab of the Delft University of TechnologyArchived 2019-10-19 at the Wayback Machine in collaboration with Wageningen University.
Air-Cobot (Aircraft Inspection enhanced by smaRt & Collaborative rOBOT) is a French research and development project of a wheeled collaborative mobile robot able to inspect aircraft during maintenance operations. This multi-partner project involves research laboratories and industry. Research around this prototype was developed in three domains: autonomous navigation, human-robot collaboration and nondestructive testing.
Genghis was a six legged insect-like robot that was created by roboticist Rodney Brooks at MIT around 1991. Brooks wanted to solve the problem of how to make robots intelligent and suggested that it is possible to create robots that displayed intelligence by using a "subsumption architecture" which is a type of reactive robotic architecture where a robot can react to the world around them. His paper "Intelligence Without Representation", which is still widely respected in the fields of robotics and Artificial Intelligence, further outlines his theories on this.