activity
20162026
most citedLocal Stability of PD Controlled Bipedal Walking Robots

35 citations · 95 across the 51 of their papers we have counts for

collaborators

61 papers

cs.RO2026

Shield-Loco: Shielding Locomotion Policies with Predictive Safety Filtering

Aditya Shirwatkar, Sebastian Sanokowski, Shishir Kolathaya +2

Reinforcement learning (RL) policies enable dynamic legged locomotion but lack mechanisms to avoid violations of safety constraints that are absent during training. Large-scale off…

cs.RO2026

Energy-Efficient Quadruped Locomotion with Compliant Feet

Pramod Pal, Shishir Kolathaya, Ashitava Ghosal

Quadruped robots are often designed with rigid feet to simplify control and maintain stable contact during locomotion. While this approach is straightforward, it limits the ability…

cs.RO2026

DTEA: A Dual-Topology Elastic Actuator Enabling Real-Time Switching Between Series and Parallel Compliance

Vishal Ramesh, Aman Singh, Shishir Kolathaya

Series and parallel elastic actuators offer complementary but mutually exclusive advantages, yet no existing actuator enables real-time transition between these topologies during o…

cs.RO2026

A Co-Design Framework for High-Performance Jumping of a Five-Bar Monoped with Actuator Optimization

Aastha Mishra, Aman Singh, Shishir Kolathaya

The performance of legged robots depends strongly on both mechanical design and control, motivating co-design approaches that jointly optimize these parameters. However, most exist…

cs.RO2026

VIP-Loco: A Visually Guided Infinite Horizon Planning Framework for Legged Locomotion

Aditya Shirwatkar, Satyam Gupta, Shishir Kolathaya

Perceptive locomotion for legged robots requires anticipating and adapting to complex, dynamic environments. Model Predictive Control (MPC) serves as a strong baseline, providing i…

cs.RO2026

Data-Driven Physics Embedded Dynamics with Predictive Control and Reinforcement Learning for Quadrupeds

Prakrut Kotecha, Aditya Shirwatkar, Shishir Kolathaya

State of the art quadrupedal locomotion approaches integrate Model Predictive Control (MPC) with Reinforcement Learning (RL), enabling complex motion capabilities with planning and…