activity
20172021
most citedA Deep Reinforcement Learning Approach for Dynamically Stable Inverse Kinematics of Humanoid Robots

6 citations · 9 across the 4 of their papers we have counts for

collaborators

8 papers

cs.RO2021

Terrain Adaptive Gait Transitioning for a Quadruped Robot using Model Predictive Control

Prathamesh Saraf, Abhishek Sarkar, Arshad Javed

Legged robots can traverse challenging terrain, use perception to plan their safe foothold positions, and navigate the environment. Such unique mobility capabilities make these pla…

cs.RO20201 cited

Omnidirectional Three Module Robot Design and Simulation

Kartik Suryavanshi, Rama Vadapalli, Praharsha Budharaja +2

This paper introduces the Omnidirectional Tractable Three Module Robot for traversing inside complex pipe networks. The robot consists of three omnidirectional modules fixed 120° a…

cs.RO2019

Omnidirectional Tractable Three Module Robot

Kartik Suryavanshi, Rama Vadapalli, Ruchitha Vucha +2

This paper introduces the Omnidirectional Tractable Three Module Robot for traversing inside complex pipe networks. The robot consists of three omnidirectional modules fixed 120° a…

cs.RO2019

Modular Pipe Climber

Rama Vadapalli, Kartik Suryavanshi, Ruchita Vucha +2

This paper discusses the design and implementation of the Modular Pipe Climber inside ASTM D1785 - 15e1 standard pipes [1]. The robot has three tracks which operate independently a…

cs.RO2018

Learning Coordinated Tasks using Reinforcement Learning in Humanoids

S Phaniteja, Parijat Dewangan, Pooja Guhan +2

With the advent of artificial intelligence and machine learning, humanoid robots are made to learn a variety of skills which humans possess. One of fundamental skills which humans…

cs.LG2018

DiGrad: Multi-Task Reinforcement Learning with Shared Actions

Parijat Dewangan, S Phaniteja, K Madhava Krishna +2

Most reinforcement learning algorithms are inefficient for learning multiple tasks in complex robotic systems, where different tasks share a set of actions. In such environments a…