Author: eya14001

Amy Thompson elected as the INCOSE New England Chapter Vice President

The University of Connecticut’s (UConn) UTC Institute for Advanced Systems Engineering (UTC-IASE) Associate Director of Academic Programs, Amy Thompson, was recently elected as the Vice President of the International Council of Systems Engineering (INCOSE) New England (NE) Chapter. Ebad Jahangir from UTRC was elected as the Secretary, Matt Tkac from CS Communication Systems was elected as President, and Ed Medri from Corindus Vascular Robotics was elected as the Treasurer.

 

INCOSE is a non-profit membership-based organization, that has dedicated it’s work since its founding in 1990 to advancing the field of systems engineering and to connect systems engineers from around the globe through a united and professional network. The main objective for INCOSE NE chapter will be to help bridge together systems engineers from all over the region across multiple different fields and domains such as energy, transport, aerospace, aviation, marine, defense, and healthcare. In conjunction with these objectives, INCOSE NE is specifically equipped to meet this objective due to the wealth and variety of industry, academic, and professional-based specialties and resources that are located within the northeast region from Connecticut to Maine. The chapter currently has 160+ systems engineering members across six states.

 

The new INCOSE NE leadership team hopes to build and sustain an invigorated atmosphere for professional growth for systems engineers and to create a strong network of resources to support the chapter in achieving their professional and organizational goals. The chapter will be (1) planning new learning opportunities, professional networking, and social networking events that will attract new members and bring-out existing members; (2) developing resources locally within the states to support local events; (3) building a network across the region with a focus on industry and business diversity; (4) working with chapters outside of the region to bring resources and value into the region; (5) instilling a renewed focus on education and workforce development; and (6) attracting engineers early in their career to get them interested in the work that INCOSE does.

 

The new INCOSE NE leadership held its first meeting on May 17th, 2018. (https://www.neincose.org/events/incose-new-england-membership-meeting-hartford) This was a multi-site meeting, which connected the new UConn-Hartford Campus site to another host site in Waltham, MA, as well as the guest speaker, David Long, and other remote viewers who could not attend in-person. At the first meeting, the new officers were introduced, a member feedback session was conducted to gauge what INCOSE NE members wanted to see from the chapter in the upcoming year, and a presentation was given by David Long, who is a past INCOSE President. Long’s presentation focused on his view of the field and discipline of systems engineering, and what we have to do as systems engineers to define and refine our roles and discipline in the development of future highly-connected, complex systems. Long proposes “the Engineering of Systems” vs. “Systems Engineering,” as a better perspective on what SE’s do.

General member meetings will begin to be held on a monthly basis, to keep members involved and active. The INCOSE NE leadership will be promoting new local sites in the future to connect and participate in meetings in New Hampshire, Rhode Island, Vermont, and Maine areas.   More information on upcoming events and other information about INCOSE NE can be found on its website: https://www.neincose.org/

 

UConn team places 2nd in the F1/10 race at Cyber-Physical Systems Week

 

For more than a year, Dr. Sridhar Duggirala, an assistant professor in the Computer Science and Engineering Department at the University of Connecticut, and his students worked on building an autonomous model racing car F1/10.   The UConn team participated in an autonomous vehicle racing competition that took place at Cyber-Physical Systems week in Porto, Portugal. In its first time in real competition, the car won 2nd place, with a lap time of 11.50 seconds.

 

The F1/10 competition is centered around creating an educational and challenging design experience for students from around the world. The competition consists of designing, constructing and testing an autonomous 1/10th scale F1 model race car, that is capable of achieving speeds upwards of 40 mph. The components of the car, such as the design of the car, the required hardware, and the bill of materials were all provided by the competition organizers. “Building the hardware for an autonomous vehicle is a long and tedious task” (Duggirala, 2018). “Additionally, it does not answer the most interesting aspect of the autonomous technology, which is the software” (Duggirala, 2018). He said that the organizers provided the design and the bill of materials to help teams’ focus on the software aspect of the autonomous vehicle, and most of the team’s time was spent on designing the software and performing testing and iteration.

 

One of the most important design mechanisms in the team’s vehicle was the Lidar technology component. This technology is used to create a visual image of their surroundings by detecting when there is an object in front of them. It then sends this information along with the visual field image to the processors, which then directs the car to avoid the obstacle in the way. Lidar technology is useful in sensing the surrounding environment and provides a very high quality resolution image of the surrounding environment. It also provides a very accurate estimate of the distance of the Lidar from a given object in the environment. The processor is the one component that takes all the inputs from the environment and the external sensing devices, such as the Lidar mechanism. Some of these inputs include distance of the car from walls and surrounding obstacles, which are then give instructions to the car to determine certain factors such as its speed and steering angle.

 

“It took us around 6 weeks to build the car.” he said. “However, testing the car was the most challenging part and it took us around 8 weeks to come up with the current controller that we have in place” (Duggirala, 2018). The team used several phases in their design process to produce the software controller design that was seen in the final product. The first phase was to develop the controller mechanism that steered the car in the right direction, that is, the direction away from all the obstacles in the car’s way. Secondly, the team developed a speed controller part that used small incremental steps to steer the car in the forward direction. Finally, the team refined the speed controller mechanism to accelerate, if there were no upcoming obstacles or turns in a reasonable distance from the car. “The biggest challenge we faced was in developing the controller for the autonomous vehicle. The accelerometer on the car was not robust, so we could not perform a procedure commonly called ‘system identification’ of the car. We overcame this by building a test track in our lab and developing various controllers to make the car accelerate, break and make the turns properly” (Duggirala, 2018).

 

The team, directed by Dr. Duggirala, consisted of Abolfazl Karimi, a PhD student from the Department of Mathematics,  Reynaldo Morillo, a PhD student from the Department of Computer Science, Nandan Tumu, an undergraduate student majoring in Computer Science, Manish Goyal, a PhD student in the Department of Computer Science and Engineering, and Bineet Ghosh, a PhD student in the Department of Computer Science and Engineering. The prize that was gifted for their second-place finish was a second-generation NVidia Tegra Processor, that the team will use to replace the central processor and build a next generation second version of the car. The team has plans to participate in the next competition at Embedded Systems Week in October of 2018. This 2.0 version will enable the team to perform systems identification and design better controllers for the car.

 

UConn engineer designs more efficient underwater tracking systems for possible naval use

 

Dr. Shalabh Gupta, an electrical engineer at the University of Connecticut, is in the process of developing a more efficient and resilient sensor network that could be used by the US Navy to detect and track underwater targets of interests, such as enemy ships and submarines. Gupta’s approach is centered around a distributed algorithm that he had developed with his PhD student James Hare that would help isolate specific sensors that are within range of the targets of interest, and switch all other sensors nodes that are not within range to low power sensing or sleeping modes.

Dr. Gupta, an engineer and a researcher at the National Institute for Undersea Vehicle Technology, is working towards an energy minimization problem that is associated with the current sensor node technology that is in use. The navy employs thousands of individual underwater acoustic sensor nodes that are the building blocks of an underwater sensor network, that is used by the navy to track underwater target movement and oceanographic conditions. In the current technology, the underwater acoustic nodes are always on and tracking, even when there are no targets in site, which expends a large amount of energy. Gupta’s algorithm is focused around turning off those sensor nodes on and off opportunistically. When a target of interest comes within range, the sensor node that is closest to that target will switch on automatically and begin tracking the target at a high-power sensing mode. This sensor that has been switched on will also use the incoming information to predict targets’ trajectory and then alert other sensors that are in the projected trajectory of the incoming target. This will in turn, switch all other sensors in the target’s path to switch on to a high-power mode, while inhibiting all the other sensors not in the trajectory from turning on. These “off” sensors will be operating at a low-power or a sleep mode while they are not in use, which will greatly reduce the amount of energy used.

Since current sensor technologies run on full power, without turning on or off, the battery life for each sensor tends to be very short and given the location of the sensors, the process of replacing the batteries continuously due to a short life span is very time consuming and difficult. When a sensor goes out, there is a loss in coverage in that part of the ocean and targets can then go undetected. Gupta is looking to implement a system that will classify the target based on its movement and then inform the other sensors in the network. Movements would be analyzed in terms of their speed, direction and magnitude, and then would be classified as either a target of interest or not. This can also be used to help reduce the amount of energy used, as the network would only track when there is a target of interest in the area, and would not turn on if there was not one present.  

While Gupta is still looking for funding to begin the construction of the underwater sensors, he has completed initial ground tests of sensor prototypes and has been in discussion with Navy officials about possibly implementing this promising technology into their underwater sensor networks.

Dr. Shalabh Gupta

Electrical Engineering