In this paper, an attempt has been made to incorporate some special features in the conventional particle swarm optimization (PSO) technique for unicycle robots with line of sight. The modified particle swarm framework (MPSF) for the self-organization of unicycle swarm robots is proposed and studied. The framework explores the benefits by dynamic associations with the proposed MPSF to realize complex swarming behaviors. In this scheme, out of sights by obstacles or neighbor robots are considered when a robot moves to a target. Each robot self-organizes to flock to the best robot in the swarm seen in its sight and migrates to a moving target while avoiding collision with obstacles and neighboring robots through the interaction of robots with line of sight. The resulting MPSF is advantageous for practical implementations since it is used for robots, even in cases where a target is blocked by obstacles or robots. Extensive simulation is presented to illustrate the viability and effectiveness of the proposed framework.