Evolution-Based Deliberative Planning for Cooperating Unmanned Ground Vehicles in a Dynamic Environment

Hussain, Talib; Montaña, David; Vidaver, Gordon

doi:10.1007/978-3-540-24855-2_113

Cited by 8 publications

(11 citation statements)

References 11 publications

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“…The ACTB approach, as presented in [1,2], was based upon the use of an evolutionary search algorithm in which domain-specific operators were applied to a variable-length representation of the paths of one or more vehicles. The representation was a plan that identified the sequence of future waypoints to be visited by each vehicle.…”

Section: Tactical Ugv Navigationmentioning

confidence: 99%

“…Each critic evaluated the plan against a specific tactical goal, such as how quickly the plan would enable the vehicles to achieve the mission objectives. In [1,2], our system only dealt with unmoving enemies and there was no imperative for real-time behavior…”

Section: Tactical Ugv Navigationmentioning

confidence: 99%

“…Gun control and firing commands were determined by an independent, opportunistic control system (i.e., automatically target and fire at nearby enemies). As in [1,2], advocates and critics for specific tactical behaviors were created. For example, we developed advocates that would encourage the UGV to stay close to walls, or look around when approaching a corner; we developed critics that would evaluate how much risk of being seen a plan put the vehicle in, or how aware of its surroundings a vehicle would be based on its planned looks.…”

Section: Tactical Ugv Navigationmentioning

confidence: 99%

See 2 more Smart Citations

Tactical UGV navigation and logistics planning

Hussain¹,

Cerys²,

Montaña³

et al. 2005

Proceedings of the 7th Annual Workshop on Genetic and Evolutionary Computation

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The Army's push towards developing highly flexible military teams that combine manned and unmanned units requires significant advances in the intelligence of the unmanned units and in the tools used to provide logistical support. BBN Technologies has recently completed a simulation-based project for the Army Research Lab in which we applied an evolutionary computation approach for determining the tactical responses of an unmanned ground vehicle, moderated by explicit rules of engagement. BBN is also currently developing a logistic analysis prototype that uses agent-based technology and evolutionary computation to enable rapid logistics planning and replanning for supporting an Army organization encountering a diversity of planned and unplanned situations.

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Section: Tactical Ugv Navigationmentioning

confidence: 99%

Section: Tactical Ugv Navigationmentioning

confidence: 99%

Section: Tactical Ugv Navigationmentioning

confidence: 99%

See 1 more Smart Citation

Tactical UGV navigation and logistics planning

Hussain¹,

Cerys²,

Montaña³

et al. 2005

Proceedings of the 7th Annual Workshop on Genetic and Evolutionary Computation

Self Cite

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show abstract

“…These group behaviors are often relatively simple, but may show impressive variability at the aggregate level over time and under different conditions in the game. Further, the use of evolutionary computation to produce highly adaptive, yet interesting and appropriate tactical behaviors in real-time has been explored for simulated combat situations with individual and small numbers of simulated military units [5,6,17]. However, creating interesting individual NPC behaviors that are relatively complex and interact meaningfully with human players has received, by contrast, little attention in the field of evolutionary computation.…”

Section: Flexible and Purposeful Npc Behaviors Using Real-time Genetimentioning

confidence: 99%

“…In [5,6], we introduced a prototype evolutionary control mechanism for unmanned ground vehicles that was designed to produce flexible tactical behaviors under a variety of conditions.…”

Section: Introductionmentioning

confidence: 99%

Flexible and Purposeful NPC Behaviors using Real-Time Genetic Control

Hussain¹,

Vidaver

2006 IEEE International Conference on Evolutionary Computation

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There is an increasing need in modern computer games for non-player characters (NPCs) with robust behaviors that achieve game objectives while appearing flexible and believable to the human players interacting with those NPCs. Evolutionary approaches to game artificial intelligence (game AI) have produced successful results for complex game winning strategies, realistic behavior patterns for groups of simulated entities, and more. However, there has been relatively little effort on evolutionary techniques for producing rich NPC behaviors for interaction with human players. To explore whether evolutionary mechanisms can support real-time control of NPCs to produce flexible and purposeful behavior, we present our initial efforts at integrating a genetic algorithm based robotic controller with an off-the-shelf game to control one or more NPCs dynamically. We describe the integration effort and our initial observations, and discuss our plan for achieving richer NPC control and for performing more detailed analysis of the behaviors of the resulting NPCs.

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Radiation search operations using scene understanding with autonomous UAV and UGV

Christie

Shoemaker

Kochersberger

et al. 2017

Journal of Field Robotics

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Autonomously searching for hazardous radiation sources requires the ability of the aerial and ground systems to understand the scene they are scouting. In this paper, we present systems, algorithms, and experiments to perform radiation search using unmanned aerial vehicles (UAV) and unmanned ground vehicles (UGV) by employing semantic scene segmentation. The aerial data is used to identify radiological points of interest, generate an orthophoto along with a digital elevation model (DEM) of the scene, and perform semantic segmentation to assign a category (e.g. road, grass) to each pixel in the orthophoto. We perform semantic segmentation by training a model on a dataset of images we collected and annotated, using the model to perform inference on images of the test area unseen to the model, and then refining the results with the DEM to better reason about category predictions at each pixel. We then use all of these outputs to plan a path for a UGV carrying a LiDAR to map the environment and avoid obstacles not present during the flight, and a radiation detector to collect more precise radiation measurements from the ground. Results of the analysis for each scenario tested favorably. We also note that our approach is general and has the potential to work for a variety of different sensing tasks.

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Evolution-Based Deliberative Planning for Cooperating Unmanned Ground Vehicles in a Dynamic Environment

Cited by 8 publications

References 11 publications

Tactical UGV navigation and logistics planning

Tactical UGV navigation and logistics planning

Flexible and Purposeful NPC Behaviors using Real-Time Genetic Control

Radiation search operations using scene understanding with autonomous UAV and UGV

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