Military Embedded Systems

Robots in the military: Brave, autonomous, and dispensable warriors

Story

February 20, 2012

Jim Davis

Cypress Semiconductor

The airspace in today's military conflicts is filled with Unmanned Aerial Vehicles of all sizes - from the hand-launched vehicles of the Special Forces to the jet-powered Predator drones flown by airmen thousands of miles away from the conflict area. On the ground are autonomous and wirelessly controlled robotic vehicles for everything from high-risk patrols to explosive ordnance detonation and disarming.

These robotic vehicles support a variety of military missions ranging from covert intelligence gathering to direct support to ground forces and overt military strikes. And this is just scratching the surface of what is moving autonomously on the battlefield. System-on-Chip (SoC) advances finetune mixed-signal designs, enabling reduced power consumption and expense.

 

The use of robots in war dates back as early as World War II with the German Goliath remote-controlled explosive vehicles and the Soviet’s wirelessly controlled, unmanned Teletanks. Today, the military robotic force also saves lives. As designers and engineers of robotic systems and components might or might not even know, they are playing a large part in enabling these and future systems. Developing these systems, however, is not a trivial task. Robotic systems, in their most basic form, simulate or otherwise artificially sense their environment and, through programmed logic, respond and interact with their surroundings. As far as complex embedded systems go, they are the ultimate mix of analog sensing, driving and digital logic, processing, and communications. While mixed-signal design is not a new concept, state-of-the-art advances in the fundamental components that make up these designs – including Systems-on-Chip (SoCs) – provide ways to implement robotic subsystems easier with lower power requirements and at greatly reduced cost.

Sensing technology for robotics

Interactions with the real world are inherently analog. A robotic system’s ability to not only accurately sense its surroundings but to do so with high resolution provides the system a stream of data inputs to more effectively enable correct decision making and response. For example, to enable a robotic sentry to effectively protect a perimeter, the system must be able to monitor and detect movement – be it through sight, sound, or touch. Through the use of a combination of high-precision thermal, IR, ultrasonic, and/or optic analog sensors, the raw input of what the robot can see can be streamed into a programmable movement detection algorithm to measure the change between snapshots and processed for the decision-making process – effectively an analog-to-digital conversion. The response itself is also an analog process (that is, a robot interacting with its environment requires movement, motors, and motor control), effectively a digital-to-analog conversion.

The brain of the robotic system lies within the digital domain. Based on the converted analog signals, the preprogrammed logical steps of responding to those signals are carried out by the robotic brain and/or externally communicated commands to the robot. For example, in a robotic sentry, after the detection algorithm feeds an alert to this brain, a series of preprogrammed logical functions is executed to steadily increase the robot’s overall alertness state. This is done by executing intimidation actions to thwart the intruder into retreating via floodlights, verbal warnings, and so on.

Historically, designs engineered for systems like a robotic sentry required sensors, costly analog discrete ADCs, amplifiers, highly accurate voltage references, DACs, PWMs, and multiple processors and microcontrollers. These are the components that make up the individual sense-detect-decide-respond-report subsystem – just one of many functions for which a robotic sentry would be responsible. The challenge in implementing just this one function is the selection of the right analog discrete components (ADCs, amps, Vrefs, DACs, and so on) designed for or compatible with the selected high-precision sensors. It can also be difficult to choose the digital components, processors, and even potentially the custom logic gates to build the alarm-level state machine to enable the appropriate decision and response. Not only is this a complicated and challenging task, but should any part of this require redefinition – perhaps swapping a sensor, adding additional sensors, adding additional response mechanisms, and so on – the same complicated task must be repeated all over again. Finally, the large number of discrete components also quickly adds up in total subsystem BOM cost and increases power requirements, doubly impacting the system because of the number of components.

Mixed-signal SoCs are key

Considering the aforementioned challenges in building a robotic system, the good news is that mixed-signal programmable SoC architectures and software tools can ease robotic design burdens. Through the integration of an analog, digital, logic, and processing core into a single mixed-signal device, designers can realize system cost savings while greatly improving the power budget. Systems-level programmability in both the analog and digital domains in these types of devices also eases the often difficult and time-consuming analog design process; these devices also provide the ability to rapidly prototype, test and, without even having to relayout designs, change and incrementally update the design along the way. For example, with systems-level programmability, tools designed at this level of design present developers with a method for defining the signal chain in a mixed-signal device and the ability to modify any part of that same signal flow as the design progresses. In this way, it becomes possible to define the signal path and configure the components at the system level via the ADC itself, using parameters such as desired resolution, sample rates, voltage reference sources, and so on. All this can be done without having to consult an analog component data book when using, for example, Cypress’s PSoC architecture and software tool, PSoC Creator (Figure 1).

 

Figure 1: Mixed-signal programmable SoC software generates an ADC based on parameters such as desired resolution, sample rate, and voltage reference source.

(Click graphic to zoom by 1.9x)


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The PSoC Creator dialog shown in Figure 1 generates an ADC based on parameters such as desired resolution, sample rate, and voltage reference source. If there are significant changes in system requirements, developers can accommodate them without any hardware modifications by adjusting these parameters and rebuilding the system application.

Mixed-signal SoC tech helps robots save the day

The military robot is a brave and autonomous warrior, and unlike its human counterpart on the battlefield, can be a dispensable asset that protects those it serves. Through the use of state-of-the-art, programmable mixed-signal SoC architectures and software, engineers can further evolve these robotic warriors with greater ease within power/cost budgets, freeing designers to apply more time and effort on the things that matter most: the robot’s core mission.

Jim Davis is Product Marketing Manager for Programmable System-on-Chip (PSoC) products at Cypress Semiconductor. He joined Cypress in 2008 and prior to that served eight years in the U.S. Air Force as a Communications Officer. He has a Bachelor’s degree in Computer Science from the U.S. Air Force Academy and a Master’s degree in Software Engineering from the University of Maryland. He can be contacted at [email protected].

Cypress Semiconductor www.cypress.com

 

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