1 citations · 1 across the 8 of their papers we have counts for
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Verification of Neural Control Barrier Functions with Symbolic Derivative Bounds Propagation
Hanjiang Hu, Yujie Yang, Tianhao Wei +1
Control barrier functions (CBFs) are important in safety-critical systems and robot control applications. Neural networks have been used to parameterize and synthesize CBFs with bo…
WeHelp: A Shared Autonomy System for Wheelchair Users
Abulikemu Abuduweili, Alice Wu, Tianhao Wei +1
There is a large population of wheelchair users. Most of the wheelchair users need help with daily tasks. However, according to recent reports, their needs are not properly satisfi…
Meta-Control: Automatic Model-based Control Synthesis for Heterogeneous Robot Skills
Tianhao Wei, Liqian Ma, Rui Chen +2
The requirements for real-world manipulation tasks are diverse and often conflicting; some tasks require precise motion while others require force compliance; some tasks require av…
Multimodal Safe Control for Human-Robot Interaction
Ravi Pandya, Tianhao Wei, Changliu Liu
Generating safe behaviors for autonomous systems is important as they continue to be deployed in the real world, especially around people. In this work, we focus on developing a no…
Robust Safe Control with Multi-Modal Uncertainty
Tianhao Wei, Liqian Ma, Ravi Pandya +1
Safety in dynamic systems with prevalent uncertainties is crucial. Current robust safe controllers, designed primarily for uni-modal uncertainties, may be either overly conservativ…
Learn With Imagination: Safe Set Guided State-wise Constrained Policy Optimization
Yifan Sun, Feihan Li, Weiye Zhao +3
Deep reinforcement learning (RL) excels in various control tasks, yet the absence of safety guarantees hampers its real-world applicability. In particular, explorations during lear…