Person:

Egerstedt, Magnus B.

Permanent Link

https://hdl.handle.net/1853/72204

Associated Organization(s)

Organizational Unit

School of Electrical and Computer Engineering

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Publication Search Results

Now showing 1 - 10 of 107

Rendezvous with Multiple, Intermittent Leaders

(Georgia Institute of Technology, 2009-12) Notarstefano, Giuseppe ; Egerstedt, Magnus B. ; Haque, Musad A.

In this paper we study bipartite, first order-networks where the nodes take on leader or follower roles. In particular, we let the leaders' positions be static and assume that they are only intermittently visible to the followers. This is an assumption that is inspired by the way female silkworm moths only intermittently release pheromones to be detected by the males. The main result in this paper states that if the followers execute the linear agreement protocol, they will converge to the convex hull spanned by the leaders (may they be visible or not).
An exploration strategy by constructing Voronoi Diagrams with provable completeness

(Georgia Institute of Technology, 2009-12) Kim, Jonghoek ; Zhang, Fumin ; Egerstedt, Magnus B.

We present novel exploration algorithms and a control law that enable the construction of Voronoi diagrams over unknown areas using a single autonomous vehicle equipped with range sensors. Our control law and exploration algorithms are provably complete. The control law uses range measurements to enable tracking Voronoi edges between two obstacles. Exploration algorithms make decisions at vertices of the Voronoi diagram to expand the explored area until a complete Voronoi diagram is constructed in finite time. MATLAB simulation results are provided to demonstrate the effectiveness of both the control law and the exploration algorithms.
Real-time optimal control of autonomous switched systems

(Georgia Institute of Technology, 2009-11-13) Ding, Xu Chu

This thesis provides a real-time algorithmic optimal control framework for autonomous switched systems. Traditional optimal control approaches for autonomous switched systems are open-loop in nature. Therefore, the switching times of the system can not be adjusted or adapted when the system parameters or the operational environments change. This thesis aims to close this loop, and apply adaptations to the optimal switching strategy based on new information that can only be captured on-line. One important contribution of this work is to provide the means to allow feedback (in a general sense) to the control laws (i.e. the switching times) of the switched system so that the control laws can be updated to maintain optimality of the switching-time control inputs. Furthermore, convergence analyses for the proposed algorithms are presented. The effectiveness of the real-time algorithms is demonstrated by an application in optimal formation and coverage control of a networked system. This application is implemented on a realistic simulation framework consisting of a number of Unmanned Aerial Vehicles (UAVs) that interact in a virtual 3D world.
Simultaneous Cooperative Exploration and Networking based on Voronoi Diagrams

(Georgia Institute of Technology, 2009-10) Kim, Jonghoek ; Zhang, Fumin ; Egerstedt, Magnus B.

We develop a strategy that enables multiple intelligent vehicles to cooperatively explore complex and dangerous territories. Every vehicle drops communication devices and expands an information network while constructing a topological map based on the Voronoi diagram. As the information network weaved by each vehicle grows, intersections eventually happen so that the networks are shared. This allows for distributed vehicles to share information with other vehicles that have also dropped communication devices. Our exploration algorithms are provably complete under mild technical assumptions. A performance analysis of the algorithms shows that in a bounded workspace, the time spent to complete the exploration decreases in proportion to the number of vehicles employed. The algorithms are demonstrated in simulation.
Curve Tracking Control for Autonomous Vehicles with Rigidly Mounted Range Sensors

(Georgia Institute of Technology, 2009-09) Kim, Jonghoek ; Zhang, Fumin ; Egerstedt, Magnus B.

In this paper, we present feedback control laws for an autonomous vehicle with rigidly mounted range sensors to track a desired curve. In particular, we consider a vehicle that has a group of rays around two center rays that are perpendicular to the velocity of the vehicle. Under such a sensor configuration, singularities are bound to occur in the curve tracking feedback control law when tracking concave curves. To overcome this singularity, we derive a hybrid strategy of switching between control laws when the vehicle gets close to singularities. Rigorous proof and extensive simulation results verify the validity of the proposed feedback control law.
A Hybrid, Multi-Agent Model of Foraging Bottlenose Dolphins

(Georgia Institute of Technology, 2009-09) Haque, Musad A. ; Rahmani, Amir R. ; Egerstedt, Magnus B.

Social behavior of animals can offer solution models for missions involving a large number of heterogeneous vehicles, such as light combat ships, unmanned aerial vehicles, and unmanned underwater vehicles. We draw inspiration from the foraging techniques of bottlenose dolphins to address the problem of heterogeneous multi-agent herding. We produce a hybrid automaton model of the entire foraging method - search, detect, and capture - where agents are modeled as first-order systems in which interactions are defined through spatial proximity. Finally, simulations are provided to illustrate that our model is expressive enough to capture this complex biological phenomenon.
CSR-EHS: Optimal, multi-modal control of complex systems

(Georgia Institute of Technology, 2009-08-20) Egerstedt, Magnus B.
Constrained Invariant Motions for Networked Multi-Agent Systems

(Georgia Institute of Technology, 2009-06) Franceschelli, Mauro ; Egerstedt, Magnus B. ; Giua, Alessandro ; Mahulea, Cristian

In this paper we propose a methodology to solve the constrained consensus problem, i.e., the consensus problem for multi-agent systems with constrained dynamics. We propose a decentralized one-step horizon optimization problem to be solved iteratively by the agents to achieve rendezvous at the centroid of the network while ensuring the connectivity of the network and the feasibility of the agents motion respect to their constrained kinematics. We also provide simulations of the algorithm behavior.
Automatic Generation of Persistent Formations for Multi-Agent Networks Under Range Constraints

(Georgia Institute of Technology, 2009-06) Smith, Brian Stephen ; Egerstedt, Magnus B. ; Howard, Ayanna M.

In this paper we present a collection of graph-based methods for determining if a team of mobile robots, subjected to sensor and communication range constraints, can persistently achieve a specified formation. What we mean by this is that the formation, once achieved, will be preserved by the direct maintenance of the smallest subset of all possible pairwise inter-agent distances. In this context, formations are defined by sets of points separated by distances corresponding to desired inter-agent distances. Further, we provide graph operations to describe agent interactions that implement a given formation, as well as an algorithm that, given a persistent formation, automatically generates a sequence of such operations. Experimental results are presented that illustrate the operation of the proposed methods on real robot platforms.
An Optimal Timing Approach to Controlling Multiple UAVs

(Georgia Institute of Technology, 2009-06) Ding, Xu Chu ; Powers, Matthew ; Egerstedt, Magnus B. ; Young, R.

In this paper we address the problem of having a single operator control a team of unmanned aerial vehicles (UAVs). This is achieved by having the team execute a leader-follower coordinated behavior, where the leader is responsible for the execution of the high-level mission. The operator interacts with the system by selecting a leader and a decision support mechanism is provided whereby the system computes the best choice of leader in the current situation. This feedback is obtained through a novel, receding horizon optimal timing control that computes an on-line estimate as to the relative merits of selecting different vehicles as leaders. The method is implemented in a dynamic, 3D simulation environment, illustrating the soundness of the proposed approach.