English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We present EWareNet, a novel intent and affect-aware social robot navigationalgorithm among pedestrians. Our approach predicts the trajectory-basedpedestrian intent from gait sequence, which is then used for intent-guidednavigation taking into account social and proxemic constraints. We propose atransformer-based model that works on commodity RGB-D cameras mounted onto amoving robot. Our intent prediction routine is integrated into a maplessnavigation scheme and makes no assumptions about the environment of pedestrianmotion. Our navigation scheme consists of a novel obstacle profilerepresentation methodology that is dynamically adjusted based on the pedestrianpose, intent, and affect. The navigation scheme is based on a reinforcementlearning algorithm that takes pedestrian intent and robot's impact onpedestrian intent into consideration, in addition to the environmentalconfiguration. We outperform current state-of-art algorithms for intentprediction from 3D gaits.

EWareNet: Emotion Aware Human Intent Prediction and Adaptive Spatial Profile Fusion for Social Robot Navigation