Rizwana Kausar — accepted AI-conference papers

2026

A Two-Stage Biologically Inspired Robot Navigation Framework via Reward-Modulated STDP and Obstacle-State Encoding

Rizwana Kausar, Vidya Sudevan, Jaime Viegas, Jorge Dias

RA-L 2026

This article presents a two-stage, biologically inspired neuromorphic framework for autonomous robot navigation in cluttered environments. The proposed architecture combines unsupervised spiking neural network (SNN)-based sensory abstraction with reward-modulated spike-timing-dependent plasticity (R

Cited by 0 Source ↗Scholar ↗

2024

Efficient Hybrid Neuromorphic-Bayesian Model for Olfaction Sensing: Detection and Classification

Rizwana Kausar, Fakhreddine Zayer, Jaime Viegas, Jorge Dias

ICRA 2024poster

Olfaction sensing in autonomous robotics faces challenges in dynamic operations, energy efficiency, and edge processing. It necessitates a machine learning algorithm capable of managing real-world odor interference, ensuring resource efficiency for mobile robotics, and accurately estimating gas feat…

Cited by 1 Source ↗Scholar ↗