no code implementations • 28 May 2023 • Eyad Shaklab, Areg Karapetyan, Arjun Sharma, Murad Mebrahtu, Mustofa Basri, Mohamed Nagy, Majid Khonji, Jorge Dias
To address the hurdles faced by existing robotic couriers, this paper introduces a customer-centric and safety-conscious LMD system for small urban communities based on AI-assisted autonomous delivery robots.
no code implementations • 18 May 2023 • Bushra Alshehhi, Areg Karapetyan, Khaled Elbassioni, Sid Chi-Kin Chau, Majid Khonji
With the electrification of transportation, the rising uptake of electric vehicles (EVs) might stress distribution networks significantly, leaving their performance degraded and stability jeopardized.
2 code implementations • 28 Feb 2023 • Mohamed Nagy, Majid Khonji, Jorge Dias, Sajid Javed
The proposed solution enables superior performance under various distortion levels in detection over current state-of-art methods.
no code implementations • 25 Feb 2023 • Rashid Alyassi, Majid Khonji
The Constrained Stochastic Shortest Path problem (C-SSP) is a formalism for planning in stochastic environments under certain types of operating constraints.
no code implementations • 29 Nov 2022 • Christopher J. Holder, Majid Khonji, Jorge Dias, Muhammad Shafique
A major challenge in machine learning is resilience to out-of-distribution data, that is data that exists outside of the distribution of a model's training data.
no code implementations • 3 Oct 2022 • Majid Khonji, Rashid Alyassi, Wolfgang Merkt, Areg Karapetyan, Xin Huang, Sungkweon Hong, Jorge Dias, Brian Williams
In this paper, we propose a risk-aware intelligent intersection system for autonomous vehicles (AVs) as well as human-driven vehicles (HVs).
no code implementations • 10 Apr 2022 • Majid Khonji
The fixed-horizon constrained Markov Decision Process (C-MDP) is a well-known model for planning in stochastic environments under operating constraints.
no code implementations • 6 Oct 2019 • Majid Khonji, Jorge Dias, Lakmal Seneviratne
Third, a planning subsystem that takes into account the uncertainty, from perception and intention recognition subsystems, and propagates all the way to control policies that explicitly bound the risk of collision.