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Rocket Landing Control with Grid Fins and Path-following using MPC

arXiv 2405.16191 ↗First posted 25 May 2024cs.AIcited by 0

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Abstract (arXiv)

In this project, we attempt to optimize a landing trajectory of a rocket. The goal is to minimize the total fuel consumption during the landing process using different techniques. Once the optimal and feasible trajectory is generated using batch approach, we attempt to follow the path using a Model Predictive Control (MPC) based algorithm, called Trajectory Optimizing Path following Estimation from Demonstration (TOPED), in order to generalize to similar initial states and models, where we introduce a novel cost function for the MPC to solve. We further show that TOPED can follow a demonstration trajectory well in practice under model mismatch and different initial states.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 12 of its 19 references that are in the map. First posted on arXiv 25 May 2024.

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12 of 19 references.

References · 12

  1. 2022FlowBot3D: Learning 3D Articulation Flow to Manipulate Articulated Objectscited by 91
  2. 2022TAX-Pose: Task-Specific Cross-Pose Estimation for Robot Manipulationcited by 47
  3. 2019Personalization of End-to-end Speech Recognition On Mobile Devices For Named Entitiescited by 41
  4. 2021Planar Robot Casting with Real2Sim2Real Self-Supervised Learningcited by 38
  5. 2023FlowBot++: Learning Generalized Articulated Objects Manipulation via Articulation Projectioncited by 34
  6. 2023DiffCLIP: Leveraging Stable Diffusion for Language Grounded 3D Classificationcited by 23
  7. 2020Robots of the Lost Arc: Self-Supervised Learning to Dynamically Manipulate Fixed-Endpoint Cablescited by 21
  8. 2021Orienting Novel 3D Objects Using Self-Supervised Learning of Rotation Transformscited by 17
  9. 20206-DoF Grasp Planning using Fast 3D Reconstruction and Grasp Quality CNNcited by 13
  10. 2022ART/ATK: A research platform for assessing and mitigating the sim-to-real gap in robotics and autonomous vehicle engineeringcited by 10
  11. 2023APLA: Additional Perturbation for Latent Noise with Adversarial Training Enables Consistencycited by 9
  12. 2019Safety Augmented Value Estimation from Demonstrations (SAVED): Safe Deep Model-Based RL for Sparse Cost Robotic Taskscited by 3

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