Abstract
Real-time whole-body controllers for legged robots typically plan through a fixed nominal model and degrade when the deployed dynamics change. Adaptive methods typically require a model structure that contact dynamics do not provide, or they need offline training for each anticipated condition. We present Look-back and Look-ahead Adaptive Model Predictive Path Integral control (LLA-MPPI). The method converts whole-body adaptation into selection over a bank of GPU-batched contact simulators with different physical or structural parameters. Windowed prediction errors select the simulator that best explains recent motion. A whole-body MPPI planner optimizes controls through the selected model. The framework requires no offline training, and its selected hypotheses are physically interpretable. Across four simulated tasks, it achieves 97.5% success while the strongest baseline reaches 74% and an oracle with the true model reaches 98.5%. Hardware validation on a Unitree Go2 shows the robot walking under a payload added mid-run, walking after one leg is disabled, and pushing a box to its goal while increasing its mass on the fly. Code, videos, and project details are available at: https://lla-control.github.io
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Cite this article
APA 7
Jung, S., AL-Sunni, M. F., Alvarez-Padilla, J., Manchester, Z., Liu, C., & Dolan, J. M. (2026). LLA-MPPI: Rapidly Adaptive Whole-body Control of Legged Robots with GPU-Accelerated Parallel Simulations. https://omanscience.com/en/articles/lla-mppi-rapidly-adaptive-whole-body-control-of-legged-robots-with-gpu-accelerated-parallel-simulations
MLA 9
Jung, Sebin, et al. "LLA-MPPI: Rapidly Adaptive Whole-body Control of Legged Robots with GPU-Accelerated Parallel Simulations." https://omanscience.com/en/articles/lla-mppi-rapidly-adaptive-whole-body-control-of-legged-robots-with-gpu-accelerated-parallel-simulations.
Chicago (author–date)
Jung, Sebin, Maitham F. AL-Sunni, Juan Alvarez-Padilla, Zachary Manchester, Changliu Liu, and John M. Dolan. 2026. "LLA-MPPI: Rapidly Adaptive Whole-body Control of Legged Robots with GPU-Accelerated Parallel Simulations." https://omanscience.com/en/articles/lla-mppi-rapidly-adaptive-whole-body-control-of-legged-robots-with-gpu-accelerated-parallel-simulations.
Harvard
Jung, S., AL-Sunni, M. F., Alvarez-Padilla, J., Manchester, Z., Liu, C. and Dolan, J. M. (2026) 'LLA-MPPI: Rapidly Adaptive Whole-body Control of Legged Robots with GPU-Accelerated Parallel Simulations', Available at: https://omanscience.com/en/articles/lla-mppi-rapidly-adaptive-whole-body-control-of-legged-robots-with-gpu-accelerated-parallel-simulations.
Vancouver
Jung S, AL-Sunni MF, Alvarez-Padilla J, Manchester Z, Liu C, Dolan JM. LLA-MPPI: Rapidly Adaptive Whole-body Control of Legged Robots with GPU-Accelerated Parallel Simulations. https://omanscience.com/en/articles/lla-mppi-rapidly-adaptive-whole-body-control-of-legged-robots-with-gpu-accelerated-parallel-simulations
IEEE
S. Jung, M. F. AL-Sunni, J. Alvarez-Padilla, Z. Manchester, C. Liu, and J. M. Dolan, "LLA-MPPI: Rapidly Adaptive Whole-body Control of Legged Robots with GPU-Accelerated Parallel Simulations," https://omanscience.com/en/articles/lla-mppi-rapidly-adaptive-whole-body-control-of-legged-robots-with-gpu-accelerated-parallel-simulations.