This study investigates consensus in sampled-data settings for second-order multi-agent systems with position constraints and switching topologies. A consensus algorithm is developed using periodically sampled position/velocity measurements, where sufficient conditions on sampling period and control parameters are established to ensure consensus achievement. Employing model transformation via state classification and system reconstruction, the nonlinear dynamics are converted into a quasi-linear form. Numerical simulations verify the efficacy of the proposed approach.