16 citations · 18 across the 9 of their papers we have counts for
10 papers · 1 filter
State and Trajectory Estimation of Tensegrity Robots via Factor Graphs and Chebyshev Polynomials
Edgar Granados, Patrick Meng, Charles Tang +4
Tensegrity robots offer compliance and adaptability, but their nonlinear, and underconstrained dynamics make state estimation challenging. Reliable continuous-time estimation of al…
Integrating Model-based Control and RL for Sim2Real Transfer of Tight Insertion Policies
Isidoros Marougkas, Dhruv Metha Ramesh, Joe H. Doerr +4
Object insertion under tight tolerances () is an important but challenging assembly task as even small errors can result in undesirable contacts. Recent effo…
Kinodynamic Trajectory Following with STELA: Simultaneous Trajectory Estimation & Local Adaptation
Edgar Granados, Sumanth Tangirala, Kostas E. Bekris
State estimation and control are often addressed separately, leading to unsafe execution due to sensing noise, execution errors, and discrepancies between the planning model and re…
: Sampling-Based Kinodynamic Replanning and Feedback Control over Approximate, Identified Models of Vehicular Systems
Aravind Sivaramakrishnan, Sumanth Tangirala, Dhruv Metha Ramesh +2
This paper aims to increase the safety and reliability of executing trajectories planned for robots with non-trivial dynamics given a light-weight, approximate dynamics model. Scen…
: Analysis of High-Dimensional Robot Controllers via Topological Tools in a Latent Space
Ewerton R. Vieira, Aravind Sivaramakrishnan, Sumanth Tangirala +3
Estimating the region of attraction () for a robot controller is essential for safe application and controller composition. Many existing methods require a closed-form e…
A Survey on the Integration of Machine Learning with Sampling-based Motion Planning
Troy McMahon, Aravind Sivaramakrishnan, Edgar Granados +1
Sampling-based methods are widely adopted solutions for robot motion planning. The methods are straightforward to implement, effective in practice for many robotic systems. It is o…