Quadruped locomotion offers significant advantages over wheeled locomotion for small mobile robots operating in challenging terrain. Central pattern generators (CPGs), as found in the neural circuitry of many animals, may be used to generate joint trajectories for quadruped robots. However, basic CPG-based trajectories do not explicitly consider ground contact constraints, a particular concern during turning maneuvers when foot slip is most likely to occur. An alternative approach proposed here is to use task-based CPGs such that ground contact constraints are enforced and foot velocities are explicitly controlled, resulting in stable omnidirectional locomotion. Further, incorporating Virtual Model Control with the task-based CPG trajectories improves the stability of the quadruped in hardware experiments.