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Unified Control Framework for Real-Time Interception and Obstacle Avoidance of Fast-Moving Objects with Diffusion Variational Autoencoder
Apan Dastider, Hao Fang, Mingjie Lin
Real-time interception of fast-moving objects by robotic arms in dynamic environments poses a formidable challenge due to the need for rapid reaction times, often within millisecon…
Hardware-Efficient Template-Based Deep CNNs Accelerator Design
Azzam Alhussain, Mingjie Lin
Acceleration of Convolutional Neural Network (CNN) on edge devices has recently achieved a remarkable performance in image classification and object detection applications. This pa…
HMT: A Hardware-Centric Hybrid Bonsai Merkle Tree Algorithm for High-Performance Authentication
Rakin Muhammad Shadab, Yu Zou, Sanjay Gandham +2
Merkle tree is a widely used tree structure for authentication of data/metadata in a secure computing system. Recent state-of-the art secure systems use a smaller-sized MT, namely…
Non-Parametric Stochastic Policy Gradient with Strategic Retreat for Non-Stationary Environment
Apan Dastider, Mingjie Lin
In modern robotics, effectively computing optimal control policies under dynamically varying environments poses substantial challenges to the off-the-shelf parametric policy gradie…
SERA: Safe and Efficient Reactive Obstacle Avoidance for Collaborative Robotic Planning in Unstructured Environments
Apan Dastider, Mingjie Lin
Safe and efficient collaboration among multiple robots in unstructured environments is increasingly critical in the era of Industry 4.0. However, achieving robust and autonomous co…
DAMON: Dynamic Amorphous Obstacle Navigation using Topological Manifold Learning and Variational Autoencoding
Apan Dastider, Mingjie Lin
DAMON leverages manifold learning and variational autoencoding to achieve obstacle avoidance, allowing for motion planning through adaptive graph traversal in a pre-learned low-dim…
Hardware-Efficient Deconvolution-Based GAN for Edge Computing
Azzam Alhussain, Mingjie Lin
Generative Adversarial Networks (GAN) are cutting-edge algorithms for generating new data samples based on the learned data distribution. However, its performance comes at a signif…