Ganga Nair B

Current work and interests

I am an M.Tech student at IISc, Bangalore. My research emphasis is on reinforcement learning–based control for quadruped locomotion, with a focus on integrating planning and learning to improve adaptability. I am currently exploring adaptive gait strategies for quadrupeds to achieve reward-driven performance. I am keen to collaborate on:

• Learning-based control
• Reinforcement learning
• Optimal control
• Legged robotics
• Mathematical modeling
• Hardware integration

News & Highlights

• Feb 17, 2026 — Visiting Kyoto University: Collaborating with Prof. Jun Morimoto on Central Pattern Generator (CPG)-based locomotion research as part of the India Japan Circulation of Talented Youths in Science Program (LOTUS).
• Dec 2025 — Presented — ICC 2025: Oral presentation on paper titled "Real-time gait adaptation for quadruped robots using RL and MPC" at the Eleventh Indian Control Conference (ICC). Details →
• Sep 2025 — Late Breaking Results — 2025 Humanoids Conference: Poster presented on "Real-time gait adaptation for quadruped robots using RL and MPC" at 2025 IEEE-RAS 24th International Conference on Humanoid Robots, Seoul, Korea.
• Aug 2025 — Received Kanaka Award Grant — 2025 Humanoids Conference: Received Kanaka Award Grant at 2025 IEEE-RAS 24th International Conference on Humanoid Robots, Seoul, Korea.
• Aug 2025 — Accepted — ICC 2025: Paper "Real-time gait adaptation for quadruped robots using RL and MPC" accepted at the Eleventh Indian Control Conference (ICC).

Robotics Projects

Real-time gait adaptation using RL and MPC

Model-free RL policies for quadruped locomotion often converge to a single gait, limiting adaptability and efficiency. We propose a control framework for real-time gait adaptation using Model Predictive Path Integral (MPPI) control and a Dreamer-based module. Our approach jointly optimizes actions and continuous gait parameters to enable smooth transitions, velocity tracking, and energy-efficient locomotion. Simulation results on the Unitree Go1 show up to 40% lower energy consumption compared to fixed-gait RL policies, while maintaining accurate tracking and stable transitions across a range of target speeds. Website → |

Energy-Efficient Quadruped Locomotion using CPG-RL

Legged animals rely on rhythmic primitives to achieve robust and efficient locomotion across diverse terrains. Inspired by this principle, we explore a hybrid locomotion framework that combines Central Pattern Generators (CPGs) with Reinforcement Learning to achieve adaptive and energy-efficient quadruped walking.

In this work, CPGs encode the underlying rhythmic structure, while a RL framework is used to modulate frequency, amplitude, and phase parameters in response to terrain and task demands. This separation introduces strong inductive bias, improving stability, reducing sample complexity, and enabling smooth transitions between locomotion patterns.

The framework is being developed in collaboration with Prof. Jun Morimoto (Kyoto University).

Model-Based Control with Online Dynamics Learning

Explored control of nonlinear systems with unknown dynamics by integrating iLQR with an online-trained neural network for dynamics estimation.

Code → |

Safe Swarm Navigation using Control Barrier Functions

Designed a control framework for multi-quadrotor swarms using Control Barrier Functions, combined with priority-based ordering to enable collision-free traversal through constrained environments.

Comparison b/w Kimera and RTAB

3D point cloud reconstruction using SLAM and subsequent semantic segmentation. Comparison to RTAB-Map for accuracy.

Formation control

Leader–follower formation control for heterogeneous multi-agent systems with real-time leader tracking.

Hardware Projects

Dynamic vibration absorber with MR Damper

Designed, fabricated, and tested a dynamic vibration absorber using a Magneto-Rheological fluid based damper. Included mathematical modelling, CAD modelling and simulation, optimisation, fabrication of test setup and experimental validation.

Repo → | Report →

Suspension for Electric All-Terrain-Vehicle

Designed, simulated and fabricated an Electric All terrain Vehicle with a focus on the suspension system. Raced the vehicle as part of E BAJA 2025.

Patents & Publications

Work Experience

Awards & Acknowledgements

• Kanaka Award Grant — IEEE Humanoids Conference 2025: Received Kanaka Award Grant at the 2025 IEEE-RAS 24th International Conference on Humanoid Robots, Seoul, Korea.
• Received Reliance Postgraduate Scholarship Selected for the prestigious Reliance Postgraduate Scholarship for 2024 as top 100 postgraduate students in India. Details →
• Axis Bank CFTI Fellowship Awarded fellowship from Axis Bank for 1st year of Masters program.
• BPO Recognitions - ExxonMobil Recognised for work on singapore Issue Management and Execution Workflow initiative and for building GP banglore Safety Identity Program.
• CREC PTA merit certificate Awarded merit certificate from CREC PTA for higest GPA in semester.

Photo Gallery

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