Transportation innovation — autonomous robots compete for glory

In September this year, two dozen autonomous robots converged on the Great Hall at the University of Technology Sydney (UTS). But don’t worry, they weren’t plotting to take over the world — they were competing in the 7th Annual National Instruments Autonomous Robotics Competition (NIARC).

NIARC is a student competition designed to encourage development and innovation in the field of robotics. Over a period of around six months, more than 120 participants from Australia, New Zealand and Singapore — ranging from first-year university students to PhD candidates — utilised an NI Robotics Development Kit to design and program intelligent vehicles that would qualify for the competition finals. The kit comprised an NI myRIO embedded measurement and control platform, the LabVIEW 2016 Robotics Software Suite and samples of the competition materials, as well as access to advice and support from NI applications engineers.

“The myRIO Student Embedded Device … includes analog inputs, analog outputs, digital I/O lines, LEDs, a push-button, an onboard accelerometer, a Xilinx FPGA, a dual-core ARM Cortex‐A9 processor and Wi-Fi support,” NI Senior Field Marketing Manager – ANZ and South East Asia Mark Phillips explained. “It is an ideal platform for this type of project or application, and it takes advantage of the same RIO architecture as our industrial platforms.

“[Participants] also receive the NI LabVIEW Robotics Module, which features an extensive robotics library with built-in connectivity to robotic sensors and actuators, foundational algorithms for intelligent operation and motion functions. The combination of this open, user-defined software and flexible hardware allows the students to create their autonomous robotics systems.

“Based on the requirements of the tasks and the track considerations, they build out their complete system by adding the mechanical build, and take advantage of a variety of I/O, such as sensors that are best suited to this kind of application: LIDAR, IR and sonar, for example, are very popular choices of sensor, as are Mecanum wheels.”

Built around the theme ‘Transportation Innovation’, in line with the rise of self-driving cars, the 2017 competition asked students to design a vehicle that could make its way through a miniature city. The robotics application areas of focus were navigation, obstacle avoidance and object handling, with participants challenged to optimise their robot’s performance to conduct a series of tasks within the least amount of time in order to earn points.

The finals saw each team’s robot set out on a confined course, with only a 2-minute time limit in which to complete as many tasks as possible. The robot began its quest by driving to a pick-up point, where a team member would drop several ‘passengers’ (in reality, small cubes) on to the robot. The more pick-up points the team chose to use, the more points they received.

The robot was then tasked with making its way through the city, which was complete with roads, buildings, barriers and other obstacles. It even had to face the equivalent of a school zone, with the LabVIEW Academy building equipped with its own ‘speed camera’ courtesy of LabVIEW and myRIO. If the robot went faster than its designated speed limit in the vicinity of the building, the act was logged and the team lost points.

“[The speed detection system] is a real-time monitoring system that takes advantage of eight infrared (IR) sensors to determine the speed of any object passing through the field,” said Phillips. “In theory, the distance between the sensors is known, so when the object passes through our sensors we calculate the time it takes to pass to the next sensor, and the algorithm in LabVIEW simply uses the following equation to determine the speed: Speed = Distance/Time.”

Once the robot got to the far end of the course, it was required to stop at a drop-off point from which its passengers could be removed. From there, it was a matter of making its way back to the beginning of the course before time ran out, continuing to avoid obstacles along the way. Once the end buzzer sounded, it was up to the judging panel to decide the winner, depending on how well each task was accomplished.

It was a long day of competition, with robots going head to head throughout the event on two identical courses. Slowly but surely, teams were knocked out — some for speeding, some for crashing and some for stalling at the starting line — until there were only two remaining: the reigning champions, from the University of Wollongong (team name UOW Robotics), and quiet achiever RMIT University (Ferrum Carrus).

The two final teams had two very different robot designs and, consequently, two very different strategies. UOW had designed a quite tall but otherwise compact robot, with the ability to move at an impressive speed and in any direction. By contrast, RMIT went with a large, circular design, similar to that of a robot vacuum cleaner. It moved slowly but precisely, in only one direction — so every time it reached a corner, it had to rotate on the spot until it was facing the right way again.

The robots set out in the first of up to three rounds. As expected, UOW reached the end of the course quickly, with RMIT still a fair distance away. But then, disaster struck — the UOW robot failed to stop at the drop-off point, thus forfeiting its points for that particular task. Then, on its journey back to the start — with passengers still in tow — it began to move off-course, causing it to crash into several obstacles. By the time the buzzer sounded, RMIT’s robot was still moving towards the drop-off point and UOW’s had left devastation in its wake. RMIT was declared the winner of Round One.

Round Two commenced much the same as Round One for the RMIT robot, which happily trundled along on its quest to the drop-off point. The UOW robot, however, could not recover its momentum. It hit a couple of obstacles en route, before eventually stalling, preventing it from proceeding any further. The team had no option but to forfeit, leaving RMIT the overall winner of the competition — and of two tickets to NIWeek 2018, to be held in in Austin, Texas, in May next year.

The surprising outcome of the final made for entertaining viewing, but it was also a clever way of educating both the participants and the event attendees about the real-life questions that arise when programming robots. Have all variables been accounted for? Should you prioritise speed over accuracy? Can your robot recover if something goes wrong?

“NI really likes this robotics competition because it gives students the opportunity to not just practise things in theory, in textbooks or on computer simulations, but really get their hands dirty, build something that’s got to work in the real world,” NI Area Sales Manager Jeremy Taylor said at the conclusion of the competition. “And as we saw, the real world doesn’t always work out exactly the same as when you do a practice.

“I think there’s something to be said for slow and steady wins the race.”

“We’re always so impressed with the talent and commitment of the NI ARC participants, and this year was no exception,” NI Marketing Director, APAC Ryota Ikeda added. “The students have proven that they have the capabilities to design and develop the smart transportation solutions of the future.

“This type of hands-on learning solidifies what the students learn in the classroom and gives them an opportunity to work with the hardware and software used by today’s top engineers. The transportation industry is just one of many that is being transformed by robotic technology, and these students will certainly have a unique advantage in helping shape the future of these industries.”

“The competition has consistently grown since its inception seven years ago, with better, faster, more efficient robots each year,” concluded Phillips. “It is always so inspiring and rewarding to see the creativity, innovation and smarts the students incorporate into their designs. Year after year, we are blown away by what they achieve in such a relatively short amount of time.

“We are looking forward to the 2018 competition, and our engineering team is already brainstorming the 2018 task and theme.”

Top image credit: ©jim/Dollar Photo Club