Major Innovations and Developments of Autonomic Machines

Academia Core Disciplines

The disciplines listed below are core to the development of autonomy, and work in conjunction with disciplines to produce results and innovations.

AI - Broadly and vaguely defined as the science of making intelligent machines. AI is an aspect of Computer Science and historically has focused on problem solving.

Robotics - This is a field of engineering and technology focused on the designing and construction of robots. It is an intersection of mechanical engineering, computer science and electrical engineering.

Control Theory - It provides a theoretical foundation to the functioning of automation in various systems, as well as in robotics in general. Control theory has given birth to important concepts like closed-loop feedback control.

Relationship with Applied Disciplines

These applied disciplines introduce a practical aspect to innovations and allows them to have a multi-pronged understanding of its surroundings.

Biology - The natural world has always been a central interest of Artificial Intelligence. AI researchers aim to use inputs from biology to improve upon machine cognition decision making in machines.

Psychology - Human Psychology provides essential benchmarks for the development and testing of machine cognition.

Linguistics - Considering that language is one of the most fascinating and complex human activities, dissecting linguistics may help researchers gain a better understanding of how the human brain functions, and in turn improve upon their AI prototypes.

State Funded R&D

United States of America USA began investing in AI and robotics in the 1950s and emerged as the pioneers of R&D in this field. The department of defense is focusing on 4 priorities when it comes to autonomous weapons development, these are:

a) improving human-machine interaction,

b) advancing machine cognition and perception,

c) teaming autonomous systems,

d) creating new V&V procedures.

Notable projects include: TRACE (Target Recognition and Adaptation in Contested Environments), CwC (Communicating with Computers), CODE (Collaborative operations in denied environments), CARACas (Control Architecture for Robotic Agent Command and Sensing), SMET (Squad Multipurpose Equipment Transport).

United Kingdom

UK is the highest investor in military R&D in all of Europe. QinetiQ and DSTL are organizations which are responsible for majority of the research in the UK. These organizations have addressed issues such as computer vision, swarming and autonomous navigation for unmanned systems.

Russia

Russia’s R&D efforts in the field of AI are predominantly military based. Russia is known to focus on military technology first and upon achieving success, adopting the technology for civilian use. Russia aims to emulate USA in the field of weapons technology, by investing billions of dollars into extensive research. Russian has attempted to speed up its projects by bringing synergy between various institutions working on AI and robotics, and allowing them to effectively work together and share important information. Russia is aiming at developing all kinds of robotics, from unmanned vehicles to nano-robots. All primarily for military applications.

France

Despite the fact that France hardly ever publicizes its military capabilities or goals, it has recently come out with the view that they will be actively participating in AI R&D for military applications to ensure that they don’t fall behind their allies as well as potential threats. Their focus remains on computer visions and intelligent sensors, in general, improving the system’s ability to effectively perceive and on it accordingly. Italy While not in concrete terms, Italy has established that modern AI technology is an aspect of their modernization plans for their army, navy and air force. They have made significant investments on the civilian aspect of AI, and many adopt a similar plan for military R&D as well.

Japan

Japan, similarly to USA, is one of the countries that are considered to be pioneers of robotics. But contrary to USA, Japan’s focus has always been on civilian applications, with a long history of industrial robots increasing the efficiency of their rapidly growing economy post World War 2. Japan is a country which truly understands and appreciates the power and usefulness of technology and robotics, as well as the rapid changes that autonomy may bring in its growth and prosperity. It is important to note that Japan’s R&D in AI is greatly restricted by its constitution. The constitution prohibits universities from conducting research for military applications.

Israel

While IDF’s budget and military R&D remains confidential, it’s no secret that IDF considers autonomous military technology as an essential area of focus, and a priority they must pursue. Israel is well known for its Hollywood style intelligence and special operations. Introducing autonomy in these fields will only increase their capabilities and reach, repel threats and maintain a proactive posture against its enemies. Israel’s R&D efforts aim to reduce human casualties in the battlefield, as well as give IDF a qualitative edge over their many enemies in the region, as they have constantly maintained over the years.

India

India did not have a formal Military AI framework till July 2017. India has a dedicated institution for R&D in AI, called Centre for AI and Robotics. Unfortunately, India’s primary focus is developing conventional weapons indigenously so as to achieve satisfactory self-sufficiency in military technology. Thus, military R&D in AI has taken a sideline for the time being.

Conclusion

What are the technical foundations of autonomy? The main findings are: Autonomy is generally interpreted as the ability of a machine to carry out tasks without human intervention. Autonomy relies primarily on software, in addition to various other technologies. Machine learning can bring major improvements in autonomy with time. What is the state of autonomy in weapon systems? The main findings are: Various military capabilities like targeting, intelligence, interoperability and health management are already making use of autonomous platforms to improve their efficiency and accuracy. There are still major human contributions to the operations conducted by autonomous systems where in the variables and constants are decided by humans beforehand. What are the relevant innovations taking place?

Key findings are: AI, robotics and control theory are driving innovation in autonomous systems USA, Russia, India and Britain are some of the countries focusing majorly on introducing autonomy into their existing military framework. Civilian industries are leaders in autonomous technology with major startups and companies focusing on AI. Resources allocated to development of autonomy by weapon manufacturers are far less than that of their civilian counterparts driving innovation for civilian use.