Skip to content
Log in
Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Oorappan G M

View on Semantic Scholar

2 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#reinforcement learning Open access Sep 2026

QMDP-PER-DDQN MATLAB Code for Mecanum Robot Trajectory Tracking under Partial Observability

MATLAB source code supporting the research article “QMDP-PER-DDQN Trajectory Tracking for Mecanum Robots under Partial Observability.” This repository provides the MATLAB implementation of a belief-aware trajectory-tracking framework for a four-Mecanum-wheel mobile robot operating under noisy and partially observable s...

Oorappan G M, Lakshmanan S A, S Vignesh · 0 citations
#reinforcement learning Open access Sep 2026

QMDP-PER-DDQN MATLAB Code for Mecanum Robot Trajectory Tracking under Partial Observability

MATLAB source code supporting the research article “QMDP-PER-DDQN Trajectory Tracking for Mecanum Robots under Partial Observability.” This repository provides the MATLAB implementation of a belief-aware trajectory-tracking framework for a four-Mecanum-wheel mobile robot operating under noisy and partially observable s...

Oorappan G M, Lakshmanan S A, S Vignesh · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.