2 citations · 2 across the 5 of their papers we have counts for
6 papers
Autonomous Navigation at the Nano-Scale: Algorithms, Architectures, and Constraints
Mahmud S. Zango, Jianglin Lan
Autonomous navigation for nano-scale unmanned aerial vehicles (nano-UAVs) is governed by extreme Size, Weight, and Power (SWaP) constraints (with the weight < 50 g and sub-100 mW o…
HOI-Dyn: Learning Interaction Dynamics for Human-Object Motion Diffusion
Lin Wu, Zhixiang Chen, Jianglin Lan
Generating realistic 3D human-object interactions (HOIs) remains a challenging task due to the difficulty of modeling detailed interaction dynamics. Existing methods treat human an…
Automatic Robot Task Planning by Integrating Large Language Model with Genetic Programming
Azizjon Kobilov, Jianglin Lan
Accurate task planning is critical for controlling autonomous systems, such as robots, drones, and self-driving vehicles. Behavior Trees (BTs) are considered one of the most promin…
Real-Time Safe Control of Neural Network Dynamic Models with Sound Approximation
Hanjiang Hu, Jianglin Lan, Changliu Liu
Safe control of neural network dynamic models (NNDMs) is important to robotics and many applications. However, it remains challenging to compute an optimal safe control in real tim…
Efficient model predictive control for nonlinear systems modelled by deep neural networks
Jianglin Lan
This paper presents a model predictive control (MPC) for dynamic systems whose nonlinearity and uncertainty are modelled by deep neural networks (NNs), under input and state constr…
Provably Robust and Plausible Counterfactual Explanations for Neural Networks via Robust Optimisation
Junqi Jiang, Jianglin Lan, Francesco Leofante +2
Counterfactual Explanations (CEs) have received increasing interest as a major methodology for explaining neural network classifiers. Usually, CEs for an input-output pair are defi…