91 citations · 524 across the 63 of their papers we have counts for
78 papers
Range Limited Coverage Control using Air-Ground Multi-Robot Teams
Max Rudolph, Sean Wilson, Magnus Egerstedt
In this paper, we investigate how heterogeneous multi-robot systems with different sensing capabilities can observe a domain with an apriori unknown density function. Common covera…
Quadratic Programming for Continuous Control of Safety-Critical Multi-Agent Systems Under Uncertainty
Si Wu, Tengfei Liu, Magnus Egerstedt +1
This paper studies the control problem for safety-critical multi-agent systems based on quadratic programming (QP). Each controlled agent is modeled as a cascade connection of an i…
Distributed Coverage Hole Prevention for Visual Environmental Monitoring with Quadcopters via Nonsmooth Control Barrier Functions
Riku Funada, María Santos, Ryuichi Maniwa +4
This paper proposes a distributed coverage control strategy for quadcopters equipped with downward-facing cameras that prevents the appearance of unmonitored areas in between the q…
A Low-complexity Brain-computer Interface for High-complexity Robot Swarm Control
Gregory Canal, Yancy Diaz-Mercado, Magnus Egerstedt +1
A brain-computer interface (BCI) is a system that allows a human operator to use only mental commands in controlling end effectors that interact with the world around them. Such a…
Optimal Stochastic Evasive Maneuvers Using the Schrodinger's Equation
Farhad Farokhi, Magnus Egerstedt
In this paper, preys with stochastic evasion policies are considered. The stochasticity adds unpredictable changes to the prey's path for avoiding predator's attacks. The prey's co…
Safe Reinforcement Learning Using Robust Control Barrier Functions
Yousef Emam, Gennaro Notomista, Paul Glotfelter +2
Reinforcement Learning (RL) has been shown to be effective in many scenarios. However, it typically requires the exploration of a sufficiently large number of state-action pairs, s…
Model Free Barrier Functions via Implicit Evading Maneuvers
Eric Squires, Rohit Konda, Samuel Coogan +1
This paper demonstrates that the safety override arising from the use of a barrier function can in some cases be needlessly restrictive. In particular, we examine the case of fixed…
A Resilient and Energy-Aware Task Allocation Framework for Heterogeneous Multi-Robot Systems
Gennaro Notomista, Siddharth Mayya, Yousef Emam +4
In the context of heterogeneous multi-robot teams deployed for executing multiple tasks, this paper develops an energy-aware framework for allocating tasks to robots in an online f…
Data-Driven Robust Barrier Functions for Safe, Long-Term Operation
Yousef Emam, Paul Glotfelter, Sean Wilson +2
Applications that require multi-robot systems to operate independently for extended periods of time in unknown or unstructured environments face a broad set of challenges, such as…
Data-Driven Adaptive Task Allocation for Heterogeneous Multi-Robot Teams Using Robust Control Barrier Functions
Yousef Emam, Gennaro Notomista, Paul Glotfelter +1
Multi-robot task allocation is a ubiquitous problem in robotics due to its applicability in a variety of scenarios. Adaptive task-allocation algorithms account for unknown disturba…
Safety With Limited Range Sensing Constraints For Fixed Wing Aircraft
Eric Squires, Rohit Konda, Pietro Pierpaoli +2
In this paper we discuss how to use a barrier function that is subject to kinematic constraints and limited sensing in order to guarantee that fixed wing unmanned aerial vehicles (…
Neural Identification for Control
Priyabrata Saha, Magnus Egerstedt, Saibal Mukhopadhyay
We present a new method for learning control law that stabilizes an unknown nonlinear dynamical system at an equilibrium point. We formulate a system identification task in a self-…
Resilient Monitoring in Heterogeneous Multi-robot Systems through Network Reconfiguration
Ragesh K. Ramachandran, Pietro Pierpaoli, Magnus Egerstedt +1
We propose a framework for resilience in a networked heterogeneous multi-robot team subject to resource failures. Each robot in the team is equipped with resources that it shares w…
Integral Control Barrier Functions for Dynamically Defined Control Laws
Aaron D. Ames, Gennaro Notomista, Yorai Wardi +1
This paper introduces integral control barrier functions (I-CBFs) as a means to enable the safety-critical integral control of nonlinear systems. Importantly, I-CBFs allow for the…
Intersection-Traffic Control of Autonomous Vehicles using Newton-Raphson Flows and Barrier Functions
Shashwat Shivam, Yorai Wardi, Magnus Egerstedt +2
This paper concerns an application of a recently-developed nonlinear tracking technique to trajectory control of autonomous vehicles at traffic intersections. The technique uses a…
A Receding Horizon Scheduling Approach for Search & Rescue Scenarios
Yousef Emam, Sean Wilson, Mathias Hakenberg +2
Many applications involving complex multi-task problems such as disaster relief, logistics and manufacturing necessitate the deployment and coordination of heterogeneous multi-agen…
Adaptive Task Allocation for Heterogeneous Multi-Robot Teams with Evolving and Unknown Robot Capabilities
Yousef Emam, Siddharth Mayya, Gennaro Notomista +2
For multi-robot teams with heterogeneous capabilities, typical task allocation methods assign tasks to robots based on the suitability of the robots to perform certain tasks as wel…
Distributed Collision-Free Motion Coordination on a Sphere: A Conic Control Barrier Function Approach
Tatsuya Ibuki, Sean Wilson, Aaron D. Ames +1
This letter studies a distributed collision avoidance control problem for a group of rigid bodies on a sphere. A rigid body network, consisting of multiple rigid bodies constrained…
Tracking Control by the Newton-Raphson Method with Output Prediction and Controller Speedup
Yorai Wardi, Carla Seatzu, Jorge Cortes +3
This paper presents a control technique for output tracking of reference signals in continuous-time dynamical systems. The technique is comprised of the following three elements: (…
Path Planning in Unknown Environments Using Optimal Transport Theory
Haoyan Zhai, Magnus Egerstedt, Haomin Zhou
This paper introduces a graph-based, potential-guided method for path planning problems in unknown environments, where obstacles are unknown until the robots are in close proximity…
A Reinforcement Learning Framework for Sequencing Multi-Robot Behaviors
Pietro Pierpaoli, Thinh T. Doan, Justin Romberg +1
Given a list of behaviors and associated parameterized controllers for solving different individual tasks, we study the problem of selecting an optimal sequence of coordinated beha…
Robust Barrier Functions for a Fully Autonomous, Remotely Accessible Swarm-Robotics Testbed
Yousef Emam, Paul Glotfelter, Magnus Egerstedt
The Robotarium, a remotely accessible swarm-robotics testbed, has provided free, open access to robotics and controls research for hundreds of users in thousands of experiments. Th…
Inferring and Learning Multi-Robot Policies by Observing an Expert
Pietro Pierpaoli, Harish Ravichandar, Nicholas Waytowich +3
We present a technique for learning how to solve a multi-robot mission that requires interaction with an external environment by observing an expert system executing the same missi…
Constraint Learning for Control Tasks with Limited Duration Barrier Functions
Motoya Ohnishi, Gennaro Notomista, Masashi Sugiyama +1
When deploying autonomous agents in unstructured environments over sustained periods of time, adaptability and robustness oftentimes outweigh optimality as a primary consideration.…