2017 NIST Agile Robotics for Industrial Automation Competition (ARIAC)

This year NIST organized a simulation based competition called Agile Robotics for Industrial Automation Competition (ARIAC). The idea was to move away from traditional robots that execute preprogrammed motion. Teams were challenged to build a system that can dynamically respond to failures in grasping, defective parts, and priority orders. Teams were expected to do this by using the minimum number of sensors. The task in the competition was focused on building assembly kits. The robot had to pick parts from bins and a conveyor and place them on automated guided vehicles.

Please see https://www.nist.gov/news-events/news/2016/01/nist-launches-international-competition-make-robots-more-agile for details on this competition.

My group fielded a team in ARIAC. Team members included Matt Buckley and Brual Shah. Competition results were announced on July 5, 2017. Please see https://www.osrfoundation.org/ariac-finals-results-announced/ for details. I am happy to report that our team won the competition.

You can check out our competition entry in the video shown below.

Effectively Utilizing Advanced Manufacturing Requires a New Approach to Closing Skills Gap

Advances in manufacturing technologies are fundamentally changing the nature of work at manufacturing enterprises. As new technologies are deployed, a large number of workers find themselves with obsolete skills and lose jobs. On the other hand, companies that are contemplating deploying new manufacturing technologies are unable to find workers with the right skills and hence many available manufacturing positions remain vacant.

The rate of rapid changes in manufacturing technologies is pointing to a future where major manufacturing technology refresh will occur every five to ten years. This means that a worker will need to face the challenge of skill obsolescence multiple times in a typical career. Overcoming this challenge using the current workforce education and training paradigm is not practical. Not finding a scalable solution to this challenge will lead to a major disruption to the way of life for the middle class.

Over the last few years, I have interacted with workers, companies, and colleges and discussed challenges and opportunities in the manufacturing workforce training area. Based on my analysis, the main challenges are the following:

1. Acquiring new manufacturing skills often requires six months or more. Displaced workers are economically vulnerable and simply do not have cash reserves to complete the training. 
2. Many displaced workers do not have math and programing prerequisites to learn advanced manufacturing technologies. Completing these prerequisites takes extra time. 
3. Many advanced manufacturing technologies are expensive. Colleges and training institutes are unable to acquire them in sufficient quantities to rapidly build the capacity needed to retrain the workforce. 
4. Workers are unable to travel to far away training locations for long periods of times to complete the training due to family constraints and/or economic considerations.

The workforce retraining will need to occur frequently. Therefore, simply relying on government grants to sustain the current training models will not suffice. Manufacturing enterprises have embraced innovations and learned how to deliver personalized products at low costs with highly compressed schedules. Once we start viewing the workforce training enterprise as a part of the manufacturing supply chain, we realize that many principles that led to significant efficiency gains in manufacturing will be applicable to the work training as well. We should aim to realize a new workforce training enterprise with the following attributes:

1. Enable trainees to participate in training remotely. 
2. Accelerate the training process. 
3. Reduce time needed to complete prerequisites. 
4. Leverage spare capacity on existing machines to reduce capital investments.

Unfortunately, there is no simple solution to meet these needs. The solution will require development of new technologies and pedagogical tools to accelerate learning, commitment from individuals to life-long learning, and cultures at companies to incentivize acquisition of new skills. Government will also need to provide education based tax credits. Colleges will need to master the agile manufacturing principles to quickly roll out new programs to meet emerging needs. Addressing the workforce training challenge this will be a step towards solving the most pressing societal problem faced by the advanced economies.

Why Automation is a Key to Innovation?

Every week I see news items that identify automation as a major threat to jobs. This is beginning to paint automation as an enemy of financial well-being of a large segment of human population. However, there is a different side to the automation story. Automation has been a major force behind many modern innovations and associated industries. Unfortunately, the connection between automation and innovation has not received much attention in the media. 

Often automation has been presented as a means to eliminate the need for humans to do dull, dangerous, and dirty tasks. Moreover, the value of automation is often rationalized in terms of cost reductions. If automation is viewed only with this lens, then it basically comes across as an instrument to replace humans with machines and hence exacerbating employment prospects for many people. In many people’s mind automation is all about “dumb” machines doing the same task over and over in a monotonous way. Innovation requires human ingenuity and creativity, so automation cannot be farther away from being an enabler for innovation. This view is too myopic and prevents people from seeing the value of automation in enabling innovations and growing new industries.
 
Automation’s biggest contribution has been in assisting humans to overcome their inherent limitations in speed, strength, size, accuracy, consistency, and reaction time. Constraints associated with human capabilities ultimately limit what types of products can be realized with manual operations. Automation presents a solution to overcome these constraints. Once we think about automation from this perspective, we realize that automation can help us in realizing products that have complex shapes and small feature sizes and require high accuracy.
 
Automation has been leveraged to create many innovative products that cannot be made using manual operations. Here are few representative examples of innovations from the medical industry that were enabled by automation:

• Computer Controlled Laser Machining: Computer controlled lasers have revolutionized machining. The software automatically controls the laser and can create really complex shapes on hard to machine metals in a matter minutes. Stents have been credited with saving many lives and they will simply not exist without computer controlled laser machining to realize complex shapes with small features.
• 3D Printing: 3D printing epitomizes automation. A computer analyzes three dimensional model of the desired part and generates instructions so that a machine can automatically build it layer by layer. Shapes that cannot be produced by any means can be realized easily using 3D printing. Customized hearing aids will simply not exist without automation. 3D printing is also enabling customized implants and prosthesis. 
• Automated Printed Circuit Board Assembly: Robots and motion control stages have revolutionized how printed circuit boards are assembled today. Automation enables printed circuit boards to utilize very small components that are packed very tightly in a confined space to create lightweight miniature electronics. The quality of life for diabetes patients will significantly deteriorate without glucose meters. Modern glucose meters rely on lightweight miniature electronics to function. These products will simply not be possible without automation in manufacturing of printed circuit board assemblies.

In summary, many innovative medical devices will simply cease to exist without the “helping hand” from automation.
 
I am concerned that all the negative press about automation will create a backlash against it. We really need advances in automation to realize the next generation products that will improve the quality of life. Automation is certainly creating challenges for the workforce and we need to find a solution to address it. However, we need to acknowledge the value of automation in driving innovations.

KUKA Innovation Award 2017

My group at the University of Southern California fielded a team in KUKA Innovation Award 2017 competition. Team members included Ariyan Kabir, Sarah Al-Hussaini, Abdullah Alsharhan, Vivek Annem, Iain Brookshaw, Qi Deng, Alec Kanyuck, Nithyananda Kumbla, Joshua Langsfeld, Rishi Malhan, Fadel Muci, Brual Shah, and Shantanu Thakar. 

After two preliminary rounds, our team was selected as one of the five finalists. Applicants for this award were expected to demonstrate an innovative robotic application using Kuka iiwa arms. Our team traveled to Hannover Messe in Germany to showcase our entry in the competition. This is one of the largest trade fair in the world. Usually, more than 250,000 visitors attend this trade fair. Distinguished visitors this year included Angela Merkel, Chancellor of Germany.

The focus of our application was automation of finishing processes such as grinding, sanding, and polishing. We combined planning, control, perception, learning, and augmented reality technologies to create a new robotic system for finishing operations. Our setup used two robots. The first robot held the part and the second robot manipulated the cleaning tool. We used external sensors to monitor the task progress.

Our application was significantly different from the traditional robotic applications in manufacturing. Robots in traditional manufacturing operations use pre-programmed motions to carry out the tasks. This idea only works when a robot is used is mass production application to make the same part over and over and this approach does not help in low volume production. An example of this is post-processing operations in additive manufacturing of custom parts. For metal based 3D printing, surface finishing operations are still manual and can take a very long time.

Angela Merkel, Chancellor of Germany walked past our booth (Image Source: Kuka)

Visitors at our Booth (Image Source: USC CAM)

Our Booth at Hannover Messe (Image Source: Kuka)

Picture at Awards Ceremony (Image Source: Kuka)

Our team with the Finalist Trophy (Image Source: USC CAM)

Manual surface finishing tasks are very tedious and time consuming and contribute significantly to the total cost in manufacturing. They also pose risks to the health of the workers. Our team believed that robots should do the tedious labor and humans should perform high level decision making in surface finishing operations. This way, we can increase the productivity of human operators and improve their quality of life.

The automated finishing system needed to manage the interaction between robots, tools, and the part to be finished. Robots needed to learn and optimize parameters on-the-fly for any given object and plan their moves. A perception system was also required for detection and localization, assessing surface quality, and ensuring safety. To achieve these goals, we integrated new planning and learning algorithms with the existing technology for perception and control.

Overall we received a lot of positive feedback on our demonstration. Many companies were interested in deploying our technology. Our team returned back to USC with a resolve to mature the technology and get it ready for deployment.

Are there any positive implications of autonomous cars on jobs in taxi industry?

Many people have raised concerns about the negative impact of autonomous cars on people’s ability to make living as Uber, Lyft, or regular taxi drivers.

Clearly autonomous cars will eliminate the need for drivers and hence people’s ability to make a living as drivers-for-hire. Let us dig a little bit deeper in this area and figure out if autonomous cars will create opportunities for people in the taxi industry to make money in some other way.

The cost associated with driving a personal car is approximately 50 cents per mile. This estimate includes the cost of a modest car, gasoline, insurance, and maintenance. The labor cost of drivers makes the cost of taxis four to six times higher. Taxi fares should go down dramatically once autonomous cars become mainstream. This will make taxi services a lot more affordable. Hopefully, this will encourage people to spend more time in taxis.

Once people start spending more time in taxis in complete privacy, they might want to spend that time more productively from work and/or leisure perspectives. Here are examples of activities that they might do in autonomous taxis:

• Doing video conferencing
• Eating
• Getting manicure/pedicures
• Personal grooming
• Watching movies
• Shopping
• Taking scenic detours
• Wine tasting
• Checking blood pressure

The above list just gives a few examples. Basically, autonomous cars will have captive customers and a wide variety of services can be offered to them by creative people. New technologies will create new service possibilities that cannot be imagined today. This should give creative people an opportunity to make money by offering services to people in autonomous taxis.

Designing such services and offering them will require a different skill set than driving. Hopefully, a proactive discussion about such service possibilities will help people get ready for the future when driving skills will be inadequate to earn a living.

I am curious to know your thoughts on what services can be offered to people spending time on autonomous taxis.