There are actually a huge number of really interesting automation research topics for university graduate students in control engineering. There are certainly too many to enumerate here, but I’ll try to set you on the right track. What you should look into depends largely on your interests and the interests of the faculty at your university.
Start by thinking about how your interests fit along a continuum ranging from the immediate practical to highly theoretical. At the practical end, there are the fields of robotics, automatically guided vehicle (AGV) development, and embedded systems.
I believe most engineering students have a good idea what robotics encompasses, and mass media are full of examples of robotic development projects. For industrial robots, probably the biggest issues involve robot programming. Specifically, it would be really nice to have more interactive ways for human engineers to show robots what to do. After all, if you were trying to get a human worker to unload a truck, you wouldn’t hand him or her a detailed list of movements to make. You wouldn’t even map out trajectories for each box to be moved. No, you’d say: “Take all of the boxes on that truck and stack them 4 high in three rows over here.” The person maps the trajectories, plans the motions, and does it. Robots can’t — at least not yet!
Fully mobile robots also share issues with AGVs. The unsolved (or at least incompletely solved) problems for AGVs start with low-level system control, such as full-authority digital engine control (FADEC), pilotage (ie, go up/down, left/right, advance/stop/reverse, etc), and progress to navigation and route planning, and (probably toughest) see-and-avoid.
Of course, the ultimate problem for AGVs and robots is mission planning. This is a skill interplanetary exploration systems could really use, but it would be helpful for any automated system. Mission planning capability would allow the supervisor (human or otherwise) to provide the robot or AGV with mission goals, then let the robot figure out how to accomplish them given current environmental constraints. For example, mission planning capability would make it possible for an Earth-based technician to tell a Mars-exploring robot to “go over there.” The robot would plan a route based on available sensory data. If it found itself entering a soft patch of ground, mission planning capability would allow it to recognise the problem, figure out how to extricate itself, then work out a strategy to find a better route.
Embedded systems automation is in its infancy. These are minimum systems insinuating themselves into major and minor appliances from cellphones to dishwashers. Issues include reduced footprint, extreme power constraints, human-machine interfacing (HMI), and communications. As technology advances along each of these dimensions, new applications become viable that just weren’t feasible before. Reduced power consumption and wireless communication, for example, has made it possible to embed sensors into structures, such as bridges and buildings, to monitor stresses and strains throughout those structures’ useful lives.
At the theoretical end of the automation-problem continuum, there are issues that, when resolved, will enable advances at the practical end. For example, applying fuzzy logic to automation algorithms would likely enable great strides toward robot mission-planning capabilities. Applying chaos theory to control problems might produce simpler and more robust control algorithms. Then, there is the whole highly esoteric question of robotic self awareness.
What you need to do is match your talents, ambitions, and capabilities with the current crop of problems being wrestled. The actor George Hamilton once pointed out that you should always do what you like to do. If you try to do anything else, you will be overshadowed by a competitor for whom what you’re doing is what they like to do. Similarly, Dr. Pitblado, my freshman psychology professor, pointed out that once you reach the university level, everyone is pretty much on par regarding capabilities. What makes one stand out compared to another is motivation. The more motivated you are for your task, the better you’ll do.
Finally, keep in mind an observation from Organisation Behavior class in MBA School: the most successful individuals are those who choose tasks that are within their capabilities, but cause them to stretch a little. Tasks that don’t make you stretch don’t move you forward. Tasks that are beyond your (current) capabilities cause you to become frustrated and stall.
The second bit of advice — pick a topic matching the interests of your university faculty — makes it possible for you to get the guidance you need to stretch in the right direction. It also gives you access to the information and resources you need to achieve your goals. Your faculty advisor has the training, experience, and motivation to help you find the right research topic for you.
*Control Engineering magazine
Charles G Masi
www.controleng.com.au