38 citations · 116 across the 17 of their papers we have counts for
24 papers
Data-Driven Optimization for Deposition with Degradable Tools
Tony Zheng, Monimoy Bujarbaruah, Francesco Borrelli
We present a data-driven optimization approach for robotic controlled deposition with a degradable tool. Existing methods make the assumption that the tool tip is not changing or i…
Output Feedback Stochastic MPC with Hard Input Constraints
Eunhyek Joa, Monimoy Bujarbaruah, Francesco Borrelli
We present an output feedback stochastic model predictive controller (SMPC) for constrained linear time-invariant systems. The system is perturbed by additive Gaussian disturbances…
Stochastic MPC with Realization-Adaptive Constraint Tightening
Hotae Lee, Monimoy Bujarbaruah, Francesco Borrelli
This paper presents a stochastic model predictive controller (SMPC) for linear time-invariant systems in the presence of additive disturbances. The distribution of the disturbance…
Safe Human-Robot Collaborative Transportation via Trust-Driven Role Adaptation
Tony Zheng, Monimoy Bujarbaruah, Yvonne R. Stürz +1
We study a human-robot collaborative transportation task in presence of obstacles. The task for each agent is to carry a rigid object to a common target position, while safely avoi…
A Simple Robust MPC for Linear Systems with Parametric and Additive Uncertainty
Monimoy Bujarbaruah, Ugo Rosolia, Yvonne R. Stürz +1
We propose a simple and computationally efficient approach for designing a robust Model Predictive Controller (MPC) for constrained uncertain linear systems. The uncertainty is mod…
Learning Environment Constraints in Collaborative Robotics: A Decentralized Leader-Follower Approach
Monimoy Bujarbaruah, Yvonne R. Stürz, Conrad Holda +2
In this paper, we propose a leader-follower hierarchical strategy for two robots collaboratively transporting an object in a partially known environment with obstacles. Both robots…
Learning How to Solve Bubble Ball
Hotae Lee, Monimoy Bujarbaruah, Francesco Borrelli
"Bubble Ball" is a game built on a 2D physics engine, where a finite set of objects can modify the motion of a bubble-like ball. The objective is to choose the set and the initial…
Traction Adaptive Motion Planning at the Limits of Handling
Lars Svensson, Monimoy Bujarbaruah, Arpit Karsolia +2
In this paper, we address the problem of motion planning and control at the limits of handling, under locally varying traction conditions. We propose a novel solution method where…
Learning to Play Cup-and-Ball with Noisy Camera Observations
Monimoy Bujarbaruah, Tony Zheng, Akhil Shetty +2
Playing the cup-and-ball game is an intriguing task for robotics research since it abstracts important problem characteristics including system nonlinearity, contact forces and pre…
Robust MPC for Linear Systems with Parametric and Additive Uncertainty: A Novel Constraint Tightening Approach
Monimoy Bujarbaruah, Ugo Rosolia, Yvonne R Stürz +2
We propose a novel approach to design a robust Model Predictive Controller (MPC) for constrained uncertain linear systems. The uncertain system is modeled as linear parameter varyi…
Learning to Satisfy Unknown Constraints in Iterative MPC
Monimoy Bujarbaruah, Charlott Vallon, Francesco Borrelli
We propose a control design method for linear time-invariant systems that iteratively learns to satisfy unknown polyhedral state constraints. At each iteration of a repetitive task…
Near-Optimal Rapid MPC using Neural Networks: A Primal-Dual Policy Learning Framework
Xiaojing Zhang, Monimoy Bujarbaruah, Francesco Borrelli
In this paper, we propose a novel framework for approximating the explicit MPC policy for linear parameter-varying systems using supervised learning. Our learning scheme guarantees…
Exploiting Model Sparsity in Adaptive MPC: A Compressed Sensing Viewpoint
Monimoy Bujarbaruah, Charlott Vallon
This paper proposes an Adaptive Stochastic Model Predictive Control (MPC) strategy for stable linear time-invariant systems in the presence of bounded disturbances. We consider mul…
Learning Robustness with Bounded Failure: An Iterative MPC Approach
Monimoy Bujarbaruah, Akhil Shetty, Kameshwar Poolla +1
We propose an approach to design a Model Predictive Controller (MPC) for constrained Linear Time Invariant systems performing an iterative task. The system is subject to an additiv…
Modeling of Dynamical Systems via Successive Graph Approximations
Siddharth H. Nair, Monimoy Bujarbaruah, Francesco Borrelli
In this work, we propose a non-parametric technique for online modeling of systems with unknown nonlinear Lipschitz dynamics. The key idea is to successively utilize measurements t…
Optimization Based Planner Tracker Design for Safety Guarantees
He Yin, Monimoy Bujarbaruah, Murat Arcak +1
We present a safe-by-design approach to path planning and control for nonlinear systems. The planner uses a low fidelity model of the plant to compute reference trajectories by sol…
A Semi-Definite Programming Approach to Robust Adaptive MPC under State Dependent Uncertainty
Monimoy Bujarbaruah, Siddharth H. Nair, Francesco Borrelli
We propose an Adaptive MPC framework for uncertain linear systems to achieve robust satisfaction of state and input constraints. The uncertainty in the system is assumed additive,…
Adaptive MPC under Time Varying Uncertainty: Robust and Stochastic
Monimoy Bujarbaruah, Xiaojing Zhang, Marko Tanaskovic +1
This paper deals with the problem of formulating an adaptive Model Predictive Control strategy for constrained uncertain systems. We consider a linear system, in presence of bounde…
Relaxed Actor-Critic with Convergence Guarantees for Continuous-Time Optimal Control of Nonlinear Systems
Jingliang Duan, Jie Li, Qiang Ge +4
This paper presents the Relaxed Continuous-Time Actor-critic (RCTAC) algorithm, a method for finding the nearly optimal policy for nonlinear continuous-time (CT) systems with known…
Safe and Near-Optimal Policy Learning for Model Predictive Control using Primal-Dual Neural Networks
Xiaojing Zhang, Monimoy Bujarbaruah, Francesco Borrelli
In this paper, we propose a novel framework for approximating the explicit MPC law for linear parameter-varying systems using supervised learning. In contrast to most existing appr…
Adaptive Trajectory Planning and Optimization at Limits of Handling
Lars Svensson, Monimoy Bujarbaruah, Nitin Kapania +1
In this paper, we tackle the problem of trajectory planning and control of a vehicle under locally varying traction limitations, in the presence of suddenly appearing obstacles. We…
Adaptive MPC for Autonomous Lane Keeping
Monimoy Bujarbaruah, Xiaojing Zhang, H. Eric Tseng +1
This paper proposes an Adaptive Robust Model Predictive Control strategy for lateral control in lane keeping problems, where we continuously learn an unknown, but constant steering…
Adaptive MPC for Iterative Tasks
Monimoy Bujarbaruah, Xiaojing Zhang, Ugo Rosolia +1
This paper proposes an Adaptive Learning Model Predictive Control strategy for uncertain constrained linear systems performing iterative tasks. The additive uncertainty is modeled…
Adaptive MPC with Chance Constraints for FIR Systems
Monimoy Bujarbaruah, Xiaojing Zhang, Francesco Borrelli
This paper proposes an adaptive stochastic Model Predictive Control (MPC) strategy for stable linear time invariant systems in the presence of bounded disturbances. We consider mul…