HyperSim: A Holistic Sim-To-Real Framework For Robust Robotic Manipulation

• URL: http://arxiv.org/abs/2605.26638v1
• Date: Tue, 26 May 2026 07:19:04 GMT
• Title: HyperSim: A Holistic Sim-To-Real Framework For Robust Robotic Manipulation
• Abstract summary: HyperSim is a holistic framework spanning from synthetic data generation to policy training and seamless real-world deployment.<n>We rigorously validate HyperSim through a large-scale empirical study involving 400 real-world task executions.<n>Our complete pipeline achieves remarkable sim-to-real success rates of 80% and 95% with ACT and _0, respectively.
• Score: 34.42333334425306
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Scaling data volume and diversity is critical for generalizing embodied intelligence. While synthetic data generation offers a scalable alternative to expensive physical data acquisition, transferring robotic manipulation policies from simulation to the real world (sim-to-real) remains a formidable challenge due to the domain gap. This paper presents HyperSim, a holistic framework spanning from synthetic data generation to policy training and seamless real-world deployment. To systematically bridge the sim-to-real gap, HyperSim is realized through three core pillars: high-fidelity environment synthesis, adversarial trajectory generation, and sim-and-real co-training. Collectively, these modules address domain discrepancies by enhancing visual fidelity, expanding data coverage, and enforcing domain-invariant representations. We rigorously validate HyperSim through a large-scale empirical study involving 400 real-world task executions across two representative manipulation models. Assessed across three fine-grained metrics, our complete pipeline achieves remarkable sim-to-real success rates of 80% and 95% with ACT and π_{0}, respectively. Furthermore, policies trained on our adversarial trajectories exhibit significantly enhanced robustness against dynamic uncertainties, achieving a 35% higher completion rate under physical perturbations.

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