Research Projects

Our lab's research spans across various domains, ranging from hardware development to the creation of controllers utilizing Optimal Controls, learning-based controls, and safety-critical controls. The following projects serve as a testament to this diverse spectrum of work.



Active Projects

Stoch BiRo

Stoch BiRo

Design and Control of a low cost bipedal robot

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Dynamic Manipulator

Dynamic Manipulator

A highly dynamic, torque controllable manipulator for quadruped robots.

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Collision Cone Control Barrier Functions (C3BF)

Collision Cone Control Barrier Functions (C3BF)

Control Barrier Functions for Kinematic Obstacle Avoidance :A Collision Cone Approach

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Force control for Robust Quadruped Locomotion: A Linear Policy Approach

Force control for Robust Quadruped Locomotion: A Linear Policy Approach

A framework for designing controllers to achieve robust blind quadrupedal walking using force control thorugh learnt linear policies.

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Energy Based Control Barrier Functions

Energy Based Control Barrier Functions

A new class of CBFs for robotic systems that augment kinetic energy with the traditional forms.

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Completed Projects

Off-Policy Average Reward Actor-Critic with Deterministic Policy Search

Off-Policy Average Reward Actor-Critic with Deterministic Policy Search

Policy gradient theorem for average reward criteria with deterministic policy.

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Dynamic Mirror Descent MPC for Model-based Model-free Reinforcement Learning

Dynamic Mirror Descent MPC for Model-based Model-free Reinforcement Learning

A framework for utilizing experience for generating predictive simulations and learning from them.

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Learning Controllers for Robust Bipedal Locomotion on Challenging Terrains

Learning Controllers for Robust Bipedal Locomotion on Challenging Terrains

A framework for sythesizing controllers to achieve blind bipedal walking on challenging terrains thorugh learnt linear policies.

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Robust Quadrupedal Locomotion on Sloped Terrains

Robust Quadrupedal Locomotion on Sloped Terrains

This paper presents a linear policy approach to achieve walking on sloped terrains

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Stoch 1

Stoch 1

A complete description of the hardware design and control architecture of our custom built quadruped robot, called the Stoch

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Active Spine on Stoch 2

Active Spine on Stoch 2

Learning Active Spine Behaviors for Dynamic and Efficient Locomotion

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Trajectory Optimization on Stoch 2

Trajectory Optimization on Stoch 2

Trajectory based Deep Policy Search for Quadrupedal Walking

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Augmented Random Search (RL Algorithm)

Augmented Random Search (RL Algorithm)

Reinforcement Learning using ARS (Augmented random Search)to generate Gaits

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