Hello, I'm Jindou Jia

I am a postdoc in the MARS Lab at Nanyang Technological University (NTU), working with Prof. Jianfei Yang. I completed my Ph.D. in 2025 from the Shenyuan Honors College, Beihang University, China. I was supervised by Prof. Lei Guo, Prof. Xiang Yu, and Prof. Kexin Guo. My research aims at generalizable robot learning. By integrating world models, generative policies, and uncertainty prediction with physical priors, I work toward robots that reliably transfer from training to unseen environments.

Scholar Github ResearchGate CV Research

News

  • Sep 2026: ๐ŸŽ‰ ADAPT has been accepted by 2026 CoRL๏ผ
  • Aug 2026: ๐ŸŽ‰ PhyFilter has been accepted by Nature npj Robotics๏ผ
  • Aug 2026: ๐ŸŽ‰ Our world model survey for robot learning has been accepted by IJRR๏ผ
  • May 2026: โญ Released MARS policy, multimodality only when it matters.
  • Apr 2026: ๐ŸŽ‰ A2A policy have been accepted by 2026 RSS๏ผ
  • Feb 2026: ๐ŸŽ‰ Two papers have been accepted by 2026 ICRA๏ผ
  • Nov 2025: ๐Ÿš€ Started my new position as a Postdoc at NTU๏ผ
  • Jul 2025: ๐ŸŽ‰ FORESEER has been accepted by IJRR๏ผ
  • Jun 2025: ๐Ÿ˜Š Passed my PhD doctoral dissertation defense๏ผ
  • Feb 2025: ๐ŸŽ‰ Feedback neural network has been selected as an oral paper by 2025 ICLR (top 1.8%)๏ผ
  • Jul 2024: ๐ŸŽ‰ Our paper, TRACE, won the Best Student Paper Award at IEEE ICCA 2024!
  • Oct 2023: ๐ŸŽ‰ EVOLVER has been accepted by T-RO๏ผ

Robotic Platforms

Hardware platforms I've worked with over the years.

Drone (2020 CEP, 2022 TAES)
2020 CEP 2022 TAES
Drone (2022 RAL)
2022 RAL
Drone (2022 RAL, 2023 TRO)
2022 RAL 2023 TRO
Drone (2025 IJRR)
2025 IJRR
VIO drone (2025 IJRR)
2025 IJRR
Grasping drone (2025 IJRR)
2025 IJRR
Drone (2025 IJRR, 2026 ICRA)
2025 IJRR 2026 ICRA
Drone (2026 arXiv)
2026 npj Robotics
Robotic arm (2023 TRO, 2026 arXiv)
2023 TRO 2026 arXiv
Robotic arm (2026 arXiv, 2026 RSS)
2026 arXiv 2026 RSS
Dual-arm system (2026 arXiv)
2026 arXiv
Quadruped robot (2026 arXiv)
2026 npj Robotics
Humanoid robot (2026 arXiv)
2026 npj Robotics 2026 CoRL
What's next?→

Publications

Showing first, co-first*, or corresponding† author papers only. Full list on Google Scholar →

Preprint

arXiv'26
APEX: Adaptive policy execution for precise manipulation

APEX: Adaptive policy execution for precise manipulation

Mengfei Zhao, Chenxi Jiang, Tuo An, Jindou Jiaโ€ , Jianfei Yangโ€ 
arXiv, 2026

APEX is a plug-and-play framework that bridges the execution gap of learned manipulation policies by reconstructing dynamically feasible references from policy outputs and adapting them online via state feedback.

Project Page PDF arXiv
arXiv'26
Feedback world model enables precise guidance of diffusion policy

Feedback world model enables precise guidance of diffusion policy

Tuo An*, Jindou Jia*, Gen Li, Jingliang Li, Chuhao Zhou, Pengfei Liu, Bofan Lyu, Jiaqi Bai, Xinying Guo, Geng Li, Jianfei Yang
arXiv, 2026

We close the predictionโ€“observation loop in world models with a lightweight feedback state that corrects future predictions online, paired with action-aware guidance to emphasize controllable dimensions, reducing prediction error by up to 76.4% and improving OOD success by 30%.

Project Page PDF arXiv Code Video
arXiv'26
FLASH: Efficient visuomotor policy via sparse sampling

FLASH: Efficient visuomotor policy via sparse sampling

Jiaqi Bai*, Jindou Jia*, Yuxuan Hu, Gen Li, Xiangyu Chen, Tuo An, Kuangji Zuo, Jianfei Yang
arXiv, 2026

We present FLASH, an efficient visuomotor policy that replaces iterative denoising with continuous Legendre polynomial trajectories, enabling single-step inference for real-time robot control.

Project Page PDF arXiv Code Video
arXiv'26
Optimizing control-friendly trajectories with self-supervised residual learning

Optimizing control-friendly trajectories with self-supervised residual learning

Kexin Guo, Zihan Yang, Yuhang Liu, Jindou Jiaโ€ , Xiang Yu
arXiv, 2026

The presented trajectory optimizer outputs trajectories that are friendly to the following control level.

PDF arXiv

2026

CoRL'26
ADAPT: Analytical disturbance-aware policy training for humanoid locomotion

ADAPT: Analytical disturbance-aware policy training for humanoid locomotion

Bofan Lyu*, Jindou Jia*, Kuangji Zuo, Yanshuo Lu, Shijia Han, Gen Li, Boyu Ma, Jingliang Li, Geng Li, Jianfei Yang
Conference on Robot Learning (CoRL), 2026

We present ADAPT, an analytical disturbance-aware framework for humanoid locomotion that infers joint-level external disturbances from robot dynamics and proprioception alone, without specialized sensors, and feeds them back into policy training for robustness to pushes, payloads, and impacts.

Project Page PDF arXiv
IJRR'26
World model for robot learning: A comprehensive survey

World model for robot learning: A comprehensive survey

Bohan Hou*, Gen Li*, Jindou Jia*, Tuo An*, Xinying Guo*, Sicong Leng, Haoran Geng, Yanjie Ze, Tatsuya Harada, Philip Torr, Oier Mees, Marc Pollefeys, Zhuang Liu, Jiajun Wu, Pieter Abbeel, Jitendra Malik, Yilun Du, Jianfei Yang
The International Journal of Robotics Research (IJRR), 2026

A comprehensive survey of world models for robot learning, covering world models as policies and as simulators across recent literature.

Project Page PDF arXiv Code
ICRA'26
Learning-based observer for coupled disturbance

Learning-based observer for coupled disturbance

Jindou Jia*, Meng Wang*, Zihan Yang, Bin Yang, Yuhang Liu, Kexin Guo, Xiang Yu
IEEE International Conference on Robotics and Automation (ICRA), 2026

We present a learning-based observer, enabling accurate prediction of the coupled disturbance consisting of internal uncertainties and external disturbances.

PDF arXiv

2025

2024

2022

T-AES'22
Agile flight control under multiple disturbances for quadrotor: Algorithms and evaluation

Agile flight control under multiple disturbances for quadrotor: Algorithms and evaluation

Jindou Jia, Kexin Guo, Xiang Yu, Lei Guo, Lihua Xie
IEEE Transactions on Aerospace and Electronic Systems (T-AES), 2022

A scheme of anti-disturbance agile flight control is developed for a maneuverable quadrotor unmanned aerial vehicle, subject to the aerodynamic drag, dynamic shift of center of gravity, and motor dynamics.

Link Video
ICUAS'22
Flight control for quadrotor safety in the presence of CoG shift and loss of motor efficiency

Flight control for quadrotor safety in the presence of CoG shift and loss of motor efficiency

Jindou Jia, Kexin Guo, Chenliang Wang, Ning Shen, Wei Jia, Xiang Yu
International Conference on Unmanned Aircraft Systems (ICUAS), 2022
Oral Presentation

A safety control strategy based on a novel nonlinear disturbance observer and geometric control is developed for a quadrotor unmanned aerial vehicle, subject to the disturbances caused by center-of-gravity shift and loss of motor efficiency.

Link Video

2020

CEP'20
Multiple observers-based anti-disturbance control for a quadrotor UAV against payload and wind disturbance

Multiple observers-based anti-disturbance control for a quadrotor UAV against payload and wind disturbance

Kexin Guo*, Jindou Jia*, Xiang Yu, Lei Guo, Lihua Xie
Control Engineering Practice, 2020

This paper presents a multiple observers-based anti-disturbance control scheme against multiple disturbances for a quadrotor unmanned aerial vehicle.

Link Video

2019

CAC'19
Dual-disturbance observers-based control of UAV subject to internal and external disturbances

Dual-disturbance observers-based control of UAV subject to internal and external disturbances

Kexin Guo*, Jindou Jia*, Xiang Yu, Lei Guo
China Automation Conference, 2019
First Prize of Outstanding Paper

This paper presents an embedded micro loop to enhance the anti-disturbance performance for unmanned aerial vehicles.

Link Video

Talks & Media

Research Interests

Robot learning World model Generative policy Uncertainty prediction
๐ŸšDrone ๐Ÿ•Quadruped robot ๐ŸฆพRobotic arm ๐Ÿค–Humanoid robot