Robots with a Human Touch



This experimental haptic interface is being used by Georgia Institute of Technology researchers.

Imagine a child who needs emergency surgery within the next couple of hours in order to survive. The problem: the only qualified surgeon is thousands of miles away. Today, this would almost certainly result in tragedy. But imagine if the surgeon could remotely operate the surgical instruments from her home hospital to save the child’s life. This modern miracle might someday be made possible via haptic robotics.

Through tactile sensation, haptic robotics enables the tool operator to literally feel a remote or virtual environment. A haptic interface provides the sensory feedback so that users can seemingly feel something that they are not physically interacting with. In this fictitious example of remote surgery, the haptic interface would provide resistance to the surgeon’s hands as the remote instruments cut into the patient’s body. The feedback would help the surgeon know when to apply more or less force to the instruments.

Typical haptic interfaces are active, meaning the system uses actuators such as motors and pneumatics to add force to the system with which the operator is interfacing. The risk presented by active haptic systems, however, is that the actuators could add too much force and injure the user. Passive haptic interfaces offer a safer alternative. Instead of adding force to the system, passive haptic interfaces remove force from the system using passive actuators such as magneto-rheological brakes.

Researchers at the Georgia Institute of Technology Intelligent Machine Dynamics Lab (IMDL) are studying the use of passive haptic systems. Dr. Wayne Book and graduate student Benjamin Black aim to show how a passive haptic system could be as effective as an active haptic system for remote operation of a device, with the additional guarantee of safety. One of the limitations of passive haptic systems, however, is that the device cannot be arbitrarily positioned, that is, the control system cannot place the haptic interface in an exact position. Book and Black are trying to overcome this limitation by developing advanced control strategies for the passive actuators.

A Graphical System Design Approach
To design and implement the advanced control strategies, Book and Black used a graphical system design approach. Graphical system design uses the combination of graphical development software tools and off-the-shelf hardware to rapidly design, prototype, and deploy embedded devices. The researchers used National Instruments (NI) LabVIEW, a graphical software development environment, to design and simulate the haptic control system and communications for remote operation. They then deployed their control strategies to real-time PXI control and acquisition systems to test the design. The advantage of this approach is that Book and Black can iterate and create a better design by avoiding low-level embedded software development and custom hardware design when deploying.

The test apparatus for this research uses a two degrees-of-freedom (DOF) manipulator that serves as the master device to control a one DOF linear motor that acts as the slave. There is no physical connection between the master and slave; rather, there is a PXI real-time control system coupled to the master and another system coupled to the slave, as shown in Figure 2. PXI System 1 executes a deterministic application programmed in NI LabVIEW that reads a gamma force sensor and two optical encoders from the master manipulator. The researchers use the data to determine the position of the master and then send that position to PXI System 2.

PXI System 2 uses the master position as the setpoint input to a 4 kilohertz PD (proportional-derivative) controller designed in LabVIEW to actuate the linear motor while reading position data from an optical encoder. The slave device encounters a physical constraint that resists its movement. The slave position is sent back to the master through UDP to PXI System 1, which feeds the data to a control algorithm, which determines the haptic force that should be applied to the user to communicate the presence of the physical constraint. The force is applied using actuation of the magneto-rheological brakes. The goal of the system is that the slave position tracks the master position.

 

Figure 2: A system diagram of the test apparatus.

Algorithm Design and Implementation
The design of the system involved several steps that were made possible by the graphical system design approach. The researchers were able to quickly import their master and slave controller algorithms into LabVIEW and then develop an interface for these algorithms with actuators and sensors using high-level programming. By instrumenting the algorithms with real hardware, they could verify theories with real-world data.

Figure 3 shows the graphical source code the researchers used to control the position of the slave. Moreover, the software tools provided high-level abstraction interfaces, such as the shared variable feature. The shared variable is a LabVIEW communication interface that abstracts the details of UDP network communication such as addressing, port management, data-type conversions, data transfer across the network, and network error handling. With these types of interfaces, engineers and scientists can concentrate on the algorithms instead of spending time on developing communication protocols.

 

Figure 3: This diagram illustrates the LabVIEW source code for the experimental slave controller.

The researchers deployed the software algorithms to PXI modular hardware systems. These systems include a deterministic, real-time controller and appropriate I/O modules that interface with sensors of the experimental haptic devices. Using the LabVIEW Real-Time Module, the researchers deployed their algorithms to the PXI controller for headless operation. They used a plug-in PXI motion control module to control the linear slave motor, and they used multifunction data acquisition devices to interface with the position sensors.

Book and Black are now improving on this research by using dynamic system simulation based on LabVIEW. Using system identification techniques, the researchers can create a mathematical model of the master and slave dynamics based on real data acquired from stimulus and response tests. They use the resulting differential equations with the LabVIEW Simulation Module, which solves the equations in time to simulate the response to different control algorithms. This simulation process helps them iterate more quickly to optimize their algorithms before applying them to the haptic devices.

Limitations in Tools, Not Know-how
Even in today’s high-tech world, innovators are more often limited by implementation tools than by a lack of knowledge. By using the graphical system design approach, however, Dr. Wayne Book and Benjamin Black have shown how to overcome this obstacle. Their work is bringing the world closer to safe haptic robotics that may someday save lives.

 

 

LabVIEW
National Instruments
Austin, TX
ni.com

 

IMDL
Georgia Institute of Technology
Atlanta, GA
imdl.gatech.edu

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Gerardo Garcia is the NI product marketing manager for LabVIEW Real-Time. Garcia holds a bachelor of science in electrical engineering from Texas A&M University. You can send an e-mail about this article here.