We are a team of legged robot enthusiasts based out of Indian Institute of Science, Bengaluru. We are mainly interested in advanced mobility in extremely challenging terrains. The team consists of technical staff members, students, interns and faculty with varying backgrounds and interests.
Policy gradient theorem for average reward criteria with deterministic policy.
Design, development and experimental realisation of a Bipedal Robot research platform: Dridh
Control Barrier Functions for Kinematic Obstacle Avoidance :A Collision Cone Approach
A framework for designing controllers to achieve robust blind quadrupedal walking using force control thorugh learnt linear policies.
A framework for utilizing experience for generating predictive simulations and learning from them.
A framework for sythesizing controllers to achieve blind bipedal walking on challenging terrains thorugh learnt linear policies.
This paper presents a linear policy approach to achieve walking on sloped terrains
A complete description of the hardware design and control architecture of our custom built quadruped robot, called the Stoch
Learning Active Spine Behaviors for Dynamic and Efficient Locomotion
Trajectory based Deep Policy Search for Quadrupedal Walking
Reinforcement Learning using ARS (Augmented random Search)to generate Gaits