UC San Diego

As the number of robotic toys on the market increases, so does the difficulty of differentiating a product from the competition. One approach to this problem is to develop robots that can interact with the user in novel ways. To this end, a relatively small, ball-catching robot was developed with a focus on low-cost components. The two main features that keep the cost low are a mobile inverted pendulum robot design, and low-cost cameras. The focus of this paper is overcoming the challenges that these two features add the the ball-catching task. Linear regression was used for estimating and predicting the ball trajectory using low-cost cameras. Three strategies for intercepting the ball with a non-holonomic robot were compared. The best strategy for the application used nonlinear model predictive control to calculate paths for the robot. A prototype was built and it successfully caught a thrown ball, but only within a limited area. Finally, improvements are suggested to increase the ball catching area of the robot, and to improve catching accuracy.