RRC is organised into research groups with staff drawn from the academic and research staff of EEE, MAE and SCE. Currently, our research areas are focused on these sectors:

• Healthcare & Assistive Robotics

• Social Robot & Human-Robot Interaction

• Industrial Robot & Manufacturing Automation

• Infrastructure Robotics

• Autonomous Systems & Unmanned Aerial Vehicles (UAV)

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Sep 21, 2024 - TURLAPATI Sri Harsha
Turlapati, Sri Harsha, 2024, "Tracing curves in the plane: geometric-invariant learning from human demonstrations", https://doi.org/10.21979/N9/QLAMWF, DR-NTU (Data), V2
The empirical laws governing human-curvilinear movements have been studied using various relationships, including minimum jerk, the 2/3 power law, and the piecewise power law. These laws quantify the speed-curvature relationships of human movements during curve tracing using crit...
Markdown Text - 1.3 KB - MD5: f1be0704e160a60a6a6e7dd5653dc968
v2
Unknown - 2.1 MB - MD5: 36465b3be0d78262b595548cf0c6b016
v2
Sep 16, 2024 - TURLAPATI Sri Harsha
Turlapati, Sri Harsha; Accoto, Dino; Domenico, Campolo, 2024, "Data for: Haptic Manipulation of 3D Scans for Geometric Feature Enhancement (Refining 3D scan of a surface by manual haptic exploration)", https://doi.org/10.21979/N9/S2JEGS, DR-NTU (Data), V1
Object localisation, shape estimation, feature detection are important sub-tasks in overarching applications like industrial tooling, assembly, manufacturing and re-manufacturing which might require robotic automation through manipulation. 3D vision techniques provide robust solu...
MATLAB Data - 3.2 KB - MD5: c63010f69bc39bd4dcf77e958000f26b
MATLAB Source Code - 975 B - MD5: 5aedd0daf0476d70264cad04ccca3e51
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