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Ilaria Torre

5 accepted papers

2023

Follow my Advice: Assume-Guarantee Approach to Task Planning with Human in the Loop

RSS 2023poster

We focus on correct-by-design robot task planning from finite Linear Temporal Logic (LTLf) specifications with a human in the loop. Since provable guarantees are difficult to obtain unconditionally, we take an assume-guarantee perspective. Along with guarantees on the robot's task satisfaction, we c…

2023

Real-Time RRT* with Signal Temporal Logic Preferences

IROS 2023poster

Signal Temporal Logic (STL) is a rigorous specification language that allows one to express various spatio-temporal requirements and preferences. Its semantics (called robustness) allows quantifying to what extent are the STL specifications met. In this work, we focus on enabling STL constraints and…

Cited by 13SourceScholar
2022

Inference of Multi-Class STL Specifications for Multi-Label Human-Robot Encounters

IROS 2022poster

This paper is interested in formalizing human trajectories in human-robot encounters. Inspired by robot navigation tasks in human-crowded environments, we consider the case where a human and a robot walk towards each other, and where humans have to avoid colliding with the incoming robot. Further, h…

Cited by 7SourceScholar
2021

Encoding Human Driving Styles in Motion Planning for Autonomous Vehicles

ICRA 2021poster

Driving styles play a major role in the acceptance and use of autonomous vehicles. Yet, existing motion planning techniques can often only incorporate simple driving styles that are modeled by the developers of the planner and not tailored to the passenger. We present a new approach to encode human…

Cited by 28SourceScholar
2021

Formalizing Trajectories in Human-Robot Encounters via Probabilistic STL Inference

IROS 2021poster

In this paper, we are interested in formalizing human trajectories in human-robot encounters. We consider a particular case where a human and a robot walk towards each other. A question that arises is whether, when, and how humans will deviate from their trajectory to avoid a collision. These human…

Cited by 7SourceScholar