My Ph.D. research focused on enabling robots to learn and adapt on-line to new tasks using reinforcement learning (RL). Performing RL on robots poses significant challenges for existing RL algorithms; such as learning in few samples, in real-time, and handling noise and delays on sensors and actuators. My thesis presented an RL algorithm called TEXPLORE which addressed these challenges and was tested on two robot platforms. I also participated in RoboCup, the international robot soccer competition where teams program robots to play soccer autonomously. I worked on all the aspects of the robot soccer problem: computer vision, localization, ball tracking, opponent tracking, humanoid motion, and multi-robot coordination. In 2012, our team won the international RoboCup competition from a field of 25 teams.