TARC: Time-Adaptive Robotic Control

arXiv:2510.23176 · cs.RO, cs.LG · Submitted 2025-10-27 · Read on arXiv

cs.RO, cs.LG

Submitted: 2025-10-27

Updated: 2026-09-15

Comments: Accepted at the 10th Conference on Robot Learning (CoRL 2026). Project page available at https://arnavsukhija.github.io/projects/tarc

Project page: https://arnavsukhija.github.io/projects/tarc

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Reinforcement Learning — 13× in this paper · explained in 4 episodes
• Reward Function — 10× in this paper · explained in 2 episodes
• Adaptation — 7× in this paper · explained in 1 episode
• Robustness — 7× in this paper · explained in 5 episodes
• Actor — 5× in this paper · explained in 3 episodes
• Time-Adaptive Robotic Control — 5× in this paper
• Adaptability — 3× in this paper · explained in 1 episode
• Deep Reinforcement Learning — 3× in this paper · explained in 2 episodes
• Reward Shaping — 3× in this paper · explained in 2 episodes
• Sim-to-Real Transfer — 3× in this paper · explained in 2 episodes
• Action Space — 2× in this paper · explained in 1 episode
• Generalization — 2× in this paper · explained in 13 episodes
• Sim-to-Real Gap — 2× in this paper · explained in 6 episodes
• Steering — 2× in this paper · explained in 2 episodes
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• IEEE International Conference on Robotics and Automation — 1× in this paper
• Markov Decision Process — 1× in this paper
• Markov Decision Process (MDP) — 1× in this paper · explained in 11 episodes
• Model Predictive Control — 1× in this paper
• Model Predictive Control (MPC) — 1× in this paper · explained in 5 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Transferability — 1× in this paper · explained in 4 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• MOSEAC: Streamlined Variable Time Step Reinforcement Learning
• Reinforcement Learning with Elastic Time Steps
• Gait-Net-augmented Implicit Kino-dynamic MPC for Dynamic Variable-frequency Humanoid Locomotion over Discrete Terrains
• Proximal Policy Optimization Algorithms
• DeepMind Control Suite
• MuJoCo Playground
• Asymmetric Actor Critic for Image-Based Robot Learning

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