8 papers · 1 filter
MUSE: Multimodal Uncertainty Quantification of State Estimation
Minkyung Kim, Henry Che, Bhargav Chandaka +6
Accurate visual state estimation has been a central topic in robotics with a wide range of applications in robot navigation, autonomous driving, and autonomous flight. Recent advan…
A Simulation Evaluation Suite for Robust Adaptive Quadcopter Control
Dingqi Zhang, Ran Tao, Sheng Cheng +2
Robust adaptive control methods are essential for maintaining quadcopter performance under external disturbances and model uncertainties. However, fragmented evaluations across tas…
DiffCoTune: Differentiable Co-Tuning for Cross-domain Robot Control
Lokesh Krishna, Sheng Cheng, Junheng Li +2
The deployment of robot controllers is hindered by modeling discrepancies due to necessary simplifications for computational tractability or inaccuracies in data-generating simulat…
Task-Parameter Nexus: Task-Specific Parameter Learning for Model-Based Control
Sheng Cheng, Ran Tao, Yuliang Gu +3
This paper presents the Task-Parameter Nexus (TPN), a learning-based approach for online determination of the (near-)optimal control parameters of model-based controllers (MBCs) fo…
Autotuning Bipedal Locomotion MPC with GRFM-Net for Efficient Sim-to-Real Transfer
Qianzhong Chen, Junheng Li, Sheng Cheng +2
Bipedal locomotion control is essential for humanoid robots to navigate complex, human-centric environments. While optimization-based control designs are popular for integrating so…
DiffTune-MPC: Closed-Loop Learning for Model Predictive Control
Ran Tao, Sheng Cheng, Xiaofeng Wang +2
Model predictive control (MPC) has been applied to many platforms in robotics and autonomous systems for its capability to predict a system's future behavior while incorporating co…