Cloud robotics is currently driving interest in both academia and industry, since it would allow robots to off-load computation intensive tasks, combine with multiple robots and even download new skills. Bandwidth allocation is the fundamental and dominant task for resource sharing among users in cloud robotics. However, many technical challenges are still outstanding, since incast congestion happens in high-bandwidth and low-latency networks, when multiple synchronized users send data to a same receiver in parallel [1]. In this paper, we introduce a resource allocation framework for cloud robotics, and propose a game-theoretic problem formulation and linear pricing scheme of bandwidth allocation, we also implement a congestion control algorithm by using optimal parameters derived from the game-theoretic algorithm. Simulation results demonstrate that the proposed mechanism achieves better performance of bandwidth allocation in cloud robotics scenarios.