Homogeneous swarm robots are of significant research interest due to their robustness, flexibility, and scalability in completing complex tasks across various applications. This article focuses on trapping heterogeneous targets using swarm robots, with emphasis on their different strengths. These targets consist of weak, strong, and group-moving individuals, where stronger targets exhibit larger body size, higher physical strength, and stronger resistance ability. Our goal is to develop an adaptive controller that enables swarm robots to self-organize and distribute themselves to trap targets, while adjusting encirclement thickness and robot group size based on target strength. We leverage local implicit information generated from density-based interaction to improve interrobot and robot–target interactions through adaptive allocation and transformation mechanisms. The feasibility of our approach is validated through numerical simulations and experiments involving up to 50 physical robots and one human-controlled transformer.