6 papers
Belief Space Planning for Risk Signal Temporal Logic via Mixed-Integer Convex Programming
Shaohang Han, Joris Verhagen, Kaier Liang +1
Signal Temporal Logic (STL) specifies robot tasks with spatio-temporal requirements, and its robustness semantics allow planning by trajectory optimization. In practice, robots est…
Risk-Aware Belief Control Barrier Functions over Random Finite Sets
Shaohang Han, Gang Chen, Yixi Cai +5
Ensuring robot safety in unknown, dynamic environments is a fundamental requirement. It involves inferring the states of an unknown and time-varying number of moving objects from n…
Exact Smooth Reformulations for Trajectory Optimization Under Signal Temporal Logic Specifications
Shaohang Han, Joris Verhagen, Jana Tumova
We study motion planning under Signal Temporal Logic (STL), a useful formalism for specifying spatial-temporal requirements. We pose STL synthesis as a trajectory optimization prob…
Risk-Aware Robot Control in Dynamic Environments Using Belief Control Barrier Functions
Shaohang Han, Matti Vahs, Jana Tumova
Ensuring safety for autonomous robots operating in dynamic environments can be challenging due to factors such as unmodeled dynamics, noisy sensor measurements, and partial observa…
Finding Control Invariant Sets via Lipschitz Constants of Linear Programs
Matti Vahs, Shaohang Han, Jana Tumova
Control invariant sets play an important role in safety-critical control and find broad application in numerous fields such as obstacle avoidance for mobile robots. However, findin…
CageCoOpt: Enhancing Manipulation Robustness through Caging-Guided Morphology and Policy Co-Optimization
Yifei Dong, Shaohang Han, Xianyi Cheng +5
Uncertainties in contact dynamics and object geometry remain significant barriers to robust robotic manipulation. Caging mitigates these uncertainties by constraining an object's m…