mlsanityData to 7 Oct 2026

TARC: Time-Adaptive Robotic Control

arXiv 2510.23176 ↗First posted 27 Oct 2025cs.RO cs.LGcited by 0

Not on the map. Why?

Abstract (arXiv)

Most robotic systems rely on fixed-frequency discrete-time controllers, creating a trade-off between the efficiency of low-frequency control and the responsiveness of high-frequency feedback. As a result, systems typically default to high control rates for robustness, at the cost of wasted inference and unnecessary actuation. Addressing this, we introduce Time-Adaptive Robotic Control (TARC), a reinforcement learning framework in which the policy jointly predicts a control action and its duration of application. TARC learns temporally extended actions by optimizing task performance under soft or hard constraints on the number of control switches, enabling adaptive modulation of control rates. We evaluate TARC on two robotic hardware platforms: a high-speed RC car and the Unitree Go1 quadruped, and on a vision-language action model in simulation, where each query incurs a costly transformer forward pass. Across all settings, TARC matches the performance of high-frequency discrete-time controllers while operating at less than half their control frequency. Unlike fixed-rate controllers, TARC adapts its control frequency online, allocating high-frequency feedback only when required.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 32 of its 51 references that are in the map. First posted on arXiv 27 Oct 2025.

Builds on

32 of 51 references.

References · 32

  1. 2017Proximal Policy Optimization Algorithmscited by 14,441
  2. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,635
  3. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusioncited by 2,730
  4. 2019Dream to Control: Learning Behaviors by Latent Imaginationcited by 1,598
  5. 2023Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardwarecited by 1,490
  6. 2017Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real Worldcited by 1,401
  7. 2023LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learningcited by 1,338
  8. 2018DeepMind Control Suitecited by 935
  9. 2019Learning agile and dynamic motor skills for legged robotscited by 402
  10. 2021Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learningcited by 395
  11. 2021Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulationcited by 375
  12. 2017Asymmetric Actor Critic for Image-Based Robot Learningcited by 202
20 more
  1. 2025Steering Your Diffusion Policy with Latent Space Reinforcement Learningcited by 149
  2. 2022Concurrent Training of a Control Policy and a State Estimator for Dynamic and Robust Legged Locomotioncited by 61
  3. 2025MuJoCo Playgroundcited by 57
  4. 2017Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learningcited by 38
  5. 2019AMZ Driverless: The Full Autonomous Racing Systemcited by 28
  6. 2020Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learningcited by 27
  7. 2021Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methodscited by 21
  8. 2020Locally Persistent Exploration in Continuous Control Tasks with Sparse Rewardscited by 12
  9. 2022Dynamic Decision Frequency with Continuous Optionscited by 11
  10. 2024When to Sense and Control? A Time-adaptive Approach for Continuous-Time RLcited by 9
  11. 2025Hold My Beer: Learning Gentle Humanoid Locomotion and End-Effector Stabilization Controlcited by 8
  12. 2022Gradient-Based Trajectory Optimization With Learned Dynamicscited by 7
  13. 2022Learning Low-Frequency Motion Control for Robust and Dynamic Robot Locomotioncited by 7
  14. 2023Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learningcited by 6
  15. 2024Bridging the Sim-to-Real Gap with Bayesian Inferencecited by 6
  16. 2020A Socially Adaptable Framework for Human-Robot Interactioncited by 3
  17. 2024Reinforcement Learning with Elastic Time Stepscited by 2
  18. 2024MOSEAC: Streamlined Variable Time Step Reinforcement Learningcited by 2
  19. 2024Variable-Frequency Model Learning and Predictive Control for Jumping Maneuvers on Legged Robotscited by 1
  20. 2025Gait-Net-augmented Implicit Kino-dynamic MPC for Dynamic Variable-frequency Humanoid Locomotion over Discrete Terrainscited by 1

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2025Robot Control Stack: A Lean Ecosystem for Robot Learning at Scale
  2. 2025Robotic World Model: A Neural Network Simulator for Robust Policy Optimization in Robotics
  3. 2026Generative Control as Optimization: Time Unconditional Flow Matching for Adaptive and Robust Robotic Control
  4. 2025DASIP: Dynamic Test-Time Compute Scaling for Robot Control with Stochastic Interpolant Policies
  5. 2026ELASTIC: Efficiently Learning to Adaptively Scale Test-Time Compute for Generative Control Policies
  6. 2020Supervised Learning and Reinforcement Learning of Feedback Models for Reactive Behaviors: Tactile Feedback Testbed
  7. 2025Control Your Robot: A Unified System for Robot Control and Policy Deployment ↗
  8. 2026TMRL: Diffusion Timestep-Modulated Pretraining Enables Exploration for Efficient Policy Finetuning