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2022/09/22 · Compared with a standard MPC policy, Performer-MPC achieves >40% better goal reached in cluttered environments and >65% better on social metrics ...
We jointly train the cost function and construct the controller relying on it, effectively solving end-to-end the corresponding bi-level optimization problem.
2022/09/10 · This paper proposes a method called performer-MPC, which uses a transformer-based learned cost function by imitation learning with visual input ...
Abstract: Despite decades of research, existing navigation systems still face real- world challenges when deployed in the wild, e.g., in cluttered home ...
Compared with a standard MPC policy,. Performer-MPC achieves >40% better goal reached in cluttered environments and >65% better on social metrics when ...
2022/09/22 · Compared with a standard MPC policy, Performer-MPC achieves >40 reached in cluttered environments and >65 navigating around humans. READ FULL ...
2023/03/03 · We introduce Performer-MPC, an end-to-end learnable robotic system that combines several mechanisms to enable real-world, robust, and adaptive robot navigation.
2023/06/07 · Model predictive control (MPC) is a popular approach for trajectory optimization in practical robotics applications.
Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation ... RT-1: ROBOTICS TRANSFORMER FOR REAL-WORLD CONTROL ...