activity
20192023
most citedSpecification-Guided Critical Scenario Identification for Automated Driving

7 citations · 23 across the 8 of their papers we have counts for

collaborators

8 papers

math.OC2023★ 7 cited

Specification-Guided Critical Scenario Identification for Automated Driving

Adam Molin, Edgar A. Aguilar, Dejan Ničković +3

To test automated driving systems, we present a case study for finding critical scenarios in driving environments guided by formal specifications. To that aim, we devise a framewor…

math.OC2023★ 3 cited

Global and Preference-based Optimization with Mixed Variables using Piecewise Affine Surrogates

Mengjia Zhu, Alberto Bemporad

Optimization problems involving mixed variables (i.e., variables of numerical and categorical nature) can be challenging to solve, especially in the presence of mixed-variable cons…

eess.SY2022

Learning Critical Scenarios in Feedback Control Systems for Automated Driving

Mengjia Zhu, Alberto Bemporad, Maximilian Kneissl +1

Testing is essential for verifying and validating control designs, especially in safety-critical applications. In particular, the control system governing an automated driving vehi…

cs.RO2022★ 2 cited

A peristaltic soft, wearable robot for compression and massage therapy

Mengjia Zhu, Adrian Ferstera, Stejara Dinulescu +4

Soft robotics is attractive for wearable applications that require conformal interactions with the human body. Soft wearable robotic garments hold promise for supplying dynamic com…

math.OC2021

C-GLISp: Preference-Based Global Optimization under Unknown Constraints with Applications to Controller Calibration

Mengjia Zhu, Dario Piga, Alberto Bemporad

Preference-based global optimization algorithms minimize an unknown objective function only based on whether the function is better, worse, or similar for given pairs of candidate…

math.OC2020★ 6 cited

Preference-based MPC calibration

Mengjia Zhu, Alberto Bemporad, Dario Piga

Automating the calibration of the parameters of a control policy by means of global optimization requires quantifying a closed-loop performance function. As this can be impractical…

cs.RO2019★ 2 cited

A Multimodal, Enveloping Soft Gripper: Shape Conformation, Bioinspired Adhesion, and Expansion-Driven Suction

Yufei Hao, Shantonu Biswas, Elliot Hawkes +4

A key challenge in robotics is to create efficient methods for grasping objects with diverse shapes, sizes, poses, and properties. Grasping with hand-like end effectors often requi…

cs.RO2019★ 3 cited

Fluidic Fabric Muscle Sheets for Wearable and Soft Robotics

Mengjia Zhu, Thanh Nho Do, Elliot Hawkes +1

Conformable robotic systems are attractive for applications in which they can be used to actuate structures with large surface areas, to provide forces through wearable garments, o…