Algorithm and Robotics
Algorithms enable Robots to learn and adapt to help completion of tasks. Massachusetts Institute of Technology (MIT) has devised an algorithm that enables a robot to quickly learn an individual’s preference for a certain task, and adapt accordingly to help complete the task. The group is using the algorithm in simulations to train robots and humans to work together.
As modern robots address real-world problems in dynamic, unstructured, and open environments, novel challenges arise in the areas of robot control algorithms and motion planning. These challenges stem from an increased need for autonomy and flexibility in robot motion and task execution. Adequate algorithms for control and motion planning will have to capture high-level motion strategies that adapt to sensor feedback.
Industrial robots today are being taught via machine learning algorithms to perform monotonous chores such as welding, assembly, disassembly, pick and place for printed circuit boards, packaging and labelling, palletizing, product inspection, testing, etc.
In the future the algorithm will be a key tool in enabling robots to recognize and respond to patterns of human movements and behaviors. Ultimately, this can help humans and robots work together in structured environments, such as factory settings and even, in some cases, the home.