Autonomous Systems
What is Autonomous System?
An autonomous system can achieve a set of goals in a changing environment – collecting information about the environment and operating for a period of time without human involvement or control.
The system must be able to do the following tasks in order to be considered autonomous:
- Monitor the environment and the current state and location of the system.
- Perceive and interpret data sources that are disparate.
- Decide what to do next and create a strategy for it.
- Avoid situations that pose a threat to human safety, property, or the autonomous system itself.
The technology of the autonomous systems is really transformative, with potential benefits of cost and risk reduction. In addition, the technology has the potential to enable completely new capabilities in environments where direct human control is not physically possible.
It should also be noted that autonomy development is a true systems engineering discipline that spans traditional engineering domains and system life-cycle phases. For these reasons, APL (Applied Physics Laboratory) has identified this technology as a key area for future development and an important part of its science and technology vision.
Some examples
- Driverless cars
- Autonomous mobile robots (AMRs)
- Autonomous flights
- Autonomous warehouse and factory systems
Autonomous Vehicles
Even though fewer trucks than passenger cars are manufactured, driverless trucks are expected to transform freight transportation and the usage of public roadways. Truck platooning is a strategy for autonomous freight transportation. In this scenario, a human driver in a tractor-trailer truck leads a convoy of driverless tractor-trailer trucks, allowing a single driver to convey significantly more cargo. Trucks using automated driver support systems can keep a specified distance from the truck in front of them. It is possible for a human driver to drop off and pick up following vehicles at specific locations along a highway.
Autonomous robots
In the health sector, robots help surgeons perform high-precision operations like coronary artery bypass surgery and cancer removal.
Systems with high mobility, such as walking robots with four legs, are able to navigate over obstacles or perform jobs that would be hazardous for humans to do. Robots for industrial inspection and robots for rescue missions are only a couple of examples.
Autonomous flights
The pilotless UAV technology is based on the autopilot technology used by commercial airline captains. Passenger aircraft that is fully automated (pilotless) is still a long way off. Similarly, unmanned aircraft (UAVs) are often piloted remotely rather than controlling their own flight routes. Airborne refueling and ground-based battery switching are two activities typically done by a completely autonomous system in UAVs.
Unmanned aerial vehicles (UAVs) or drones are self-flying, autonomous aircraft. Drones have been used for observation, mapping, asset inspection, and environmental research for many years already.
Sensor fusion – an important element of Autonomous System
Each type of sensor and source of environmental data has its own set of benefits and limitations. Sensor fusion provides more complete and precise information about the environment than a single source could. Sensor fusion, a perception-focused area of machine learning and signal processing, integrates input from many sensors and databases to create higher-quality information so that an autonomous system can make better, safer decisions. Sensor fusion can also be referred to as data fusion, filtering, or target tracking.
How does Sensor Fusion work?
Sensor fusion systems combine data from cameras, LiDAR, radar, sonar, and other sensors, effectively augmenting data from one sensor with data from another. The large amount of sensor data that has to be processed for rapid decision-making by an autonomous system is handled by highly efficient, high-throughput software and special-purpose hardware known as accelerators.
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