University of Pennsylvania
Department of Electrical and Systems Engineering
ESE SENIOR DESIGN PROJECT - ADVISOR PROJECT SUBMISSION FORM
1. Project Title: Hierarchical Information Routing in Dynamic Multi-Agent
Systems
2. Proposer's Name: Daniel E. Koditschek, Omur Arslan
E-mail: {kod,omur}@seas.upenn.edu
Are you willing and able to serve as advisor for this project? _X_ Yes; ___ No
Omur would be the Front Line Mentor with backup from Dan
3. Brief Project Description:
Notwithstanding their obvious advantages relative to solitary robots, multi-agent systems
introduce new challenges requiring efficient and effective solutions for cooperative behaviors,
information aggregation, collective decision making and communication. This project aims to
design hierarchical information routing methods for mobile multi-agent systems and to
evaluate and quantify their performance in an extensible simulation environment built to
study practical engineering applications such as distributed sensor fusion and estimation,
anomaly detection, coordinated exploration and mapping or environmental monitoring.
As the prime motivating setting, consider the problem of multi-robot exploration and mapping
in an unknown environment [1],[5],[6]. The integration of individuals’ perceptual constructs
(e.g, landmarks or new objects) into a consistent, global map plays a crucial role in such a
coordinated exploration and mapping task. To increase efficiency and promote acquisition of
new but accurate information, the integration should weigh likely redundancy against task
relevance and prioritize the aggregation of local data in assembling the global view.
A common method of information collection and routing in stationary wireless sensor
networks uses hierarchical clustering of the sensor nodes based on their proximity [2].
Considering a multi-agent mapping problem as a mobile sensor network task motivates
exploring analogous hierarchical routing protocols as the basis for a systematic and efficient
communications and perceptual integration methodology in settings of distributed robot
exploration.
One of the critical challenges for mobile agents is that their clustering hierarchy dynamically
changes as the agents move, introducing the need for distributed tracking of the clustering
tree. Fortunately, it has been known for decades that the relation between minimum spanning
trees and single linkage clustering [3,4] yields one such distributed clustering scheme. Hence,
a baseline solution for the coordinated mapping task might use such a distributed method [3],
in a greedy manner to track the change in clustering hierarchy of the agents by performing re-
clustering as required along their collective motion trajectories. Other hierarchical clustering
methods of interest to the project proposers could then be considered and compared.
4. Project Design Objectives:
(1) Design and implement a computational engine (either from a fresh start or by adapting
one already extant [6],[7],[8]) for simulation study of hierarchically-coordinated multirobot exploration and mapping. The engine should permit ready specification of varied
indoor or outdoor spatial environments as well as managing algorithms for driving
multiple autonomous agents with varied mobility and perceptual capabilities as
exemplified in the recent literature [1],[5],[6].
(2) Implement within this simulation environment an instance of the greedy distributed
hierarchical clustering method [3,4] for tracking the time varying cluster hierarchy tree
arising from the changing configurations of the agents within their environment.
(3) Design with consultation from the project proposers an alternative distributed
hierarchical clustering method and an evaluation tool for comparing its (and future
alternative schemes’) performance against that of the default greedy method.
(4) Design with consultation from the project proposers a sample data integration protocol
built over the alternative distributed hierarchical clustering methods (2) and (3) and use
it to run comparative simulations of: (i) hierarchical map merging, and (ii)
hierarchically-coordinated exploration.
(5) Evaluate with consultation from the project proposers the effect of various cluster-head
(i.e., representative agent of each cluster) selection methods , on the performance of the
data integration protocol in (4).
5. Project Prerequisites:
What specific knowledge (e.g. courses or topics) and skills (e.g. programming languages or
software packages) will this project require? Please rank order the knowledge and skills you
have identified, with the most important at the top of the list.
Advanced Programming Skills (familiarity with C/C++, Matlab, OpenCV, ROS)
Computer Networks (especially channel access methods)
Robot Motion Control and Planning Methods
Probability Theory and Bayesian Statistics
Simultaneous Localization and Mapping (SLAM) Methods
6. References:
[1] Fox, D., Ko, J., Konolige, K., Limketkai, B., Schulz, D., & Stewart, B. "Distributed multirobot
exploration and mapping." Proceedings of the IEEE 94.7 (2006): 1325-1339.
[2] Akkaya, Kemal, and Mohamed Younis. "A survey on routing protocols for wireless sensor
networks." Ad hoc networks 3.3 (2005): 325-349.
[3] Gallager, Robert G., Pierre A. Humblet, and Philip M. Spira. "A distributed algorithm for
minimum-weight spanning trees." ACM Transactions on Programming Languages and systems
(TOPLAS) 5.1 (1983): 66-77.
[4] Gower, John C., and G. J. S. Ross. "Minimum spanning trees and single linkage cluster
analysis." Applied statistics (1969): 54-64.
[5] M. A. Hsieh, A. Cowley, J. F. Keller, L. Chaimowicz, B. Grocholsky, V. Kumar, C. J. Taylor, Y.
Endo, R. C. Arkin, B. Jung, D. F. Wolf, G. S. Sukhatme, and D. C. MacKenzie, “Adaptive teams of
autonomous aerial and ground robots for situational awareness,” Journal of Field Robotics, vol. 24, no.
11–12, pp. 991–1014, 2007.
[6] J. Butzke, K. Daniilidis, A. Kushleyev, D. D. Lee, M. Likhachev, C. Phillips, and M. Phillips, “The
University of Pennsylvania MAGIC 2010 multi-robot unmanned vehicle system,” Journal of Field
Robotics, vol. 29, no. 5, pp. 745–761, 2012.
[7] Koenig, Nathan, and Andrew Howard. "Design and use paradigms for gazebo, an opensource multi-robot simulator." Intelligent Robots and Systems, 2004.(IROS 2004). Proceedings.
2004 IEEE/RSJ International Conference on. Vol. 3. IEEE, 2004.
[8] Richard Vaughan. "Massively Multiple Robot Simulations in Stage", Swarm Intelligence
2(2-4):189-208, 2008. Springer.