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"... Algorithms are a fundamental component of robotic systems – they control or reason about motion and perception in the physi-cal world, they receive input from noisy sensors, consider geometric and physical constraints, and operate on the world through imprecise actuators. Increasingly, robotics algo ..."
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Algorithms are a fundamental component of robotic systems – they control or reason about motion and perception in the physi-cal world, they receive input from noisy sensors, consider geometric and physical constraints, and operate on the world through imprecise actuators. Increasingly, robotics algorithms are finding use in areas far beyond the traditional scope of ro-bots such as computer animation and gaming, virtual environ-ments, sensor networks, manufacturing, medical robotics, and computational biology. The International Workshop on the Algorithmic Founda-tions of Robotics (WAFR) is a multi-disciplinary single-track workshop with submitted and invited papers on advances on algorithmic problems in robotics. WAFR has been held every other year since 1994 and has an established reputation as one of the most important venues for presenting algorithmic work related to robotics. Previous WAFRs have been held at Zeist,
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, 2015
"... Abstract — This tutorial contains tools and techniques for designing pursuit and evasion strategies. The material targets a diverse audience including STEM educators as well as robotics researchers interested in applications of pursuit-evasion games. We start with a simple “lion and man ” game in a ..."
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Abstract — This tutorial contains tools and techniques for designing pursuit and evasion strategies. The material targets a diverse audience including STEM educators as well as robotics researchers interested in applications of pursuit-evasion games. We start with a simple “lion and man ” game in a square environment which should be accessible to anyone with a high-school level background on geometry and trigonometry. We then visit various versions of this game with increasing complexity. Rather than surveying specific results for specific environments, the tutorial highlights broadly applicable tech-niques and strategies. It also includes exercises for STEM educators as well as open problems for robotics researchers. I.
On the Value of Information in a Differential Pursuit-Evasion Game
"... Abstract — In this paper, we address the pursuit/evasion prob-lem of capturing an omnidirectional evader using a Differential Drive Robot (DDR) in an obstacle-free environment. The goal of the evader is to keep the pursuer farther than the capture distance for as long as possible and for the pursuer ..."
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Abstract — In this paper, we address the pursuit/evasion prob-lem of capturing an omnidirectional evader using a Differential Drive Robot (DDR) in an obstacle-free environment. The goal of the evader is to keep the pursuer farther than the capture distance for as long as possible and for the pursuer the goal is to capture the evader as soon as possible. In [1] an open-loop time-optimal strategy is proposed for this pursuit/evasion problem. In [2] a state feedback-based time-optimal motion policy for the DDR is provided. The time-optimal strategies obtained in [1] are in Nash equilibrium, meaning that any unilateral deviation of a player from the optimal strategies does not provide it a benefit in its payoff. However, Nash equilibrium does not tell if one player deviates from its optimal policy then, does there exist a new strategy for the other player that can take advantage of such deviation? If so, which is the required information to improve the payoff compared with the worst case scenario? In this paper we address those questions, analysing the scenario in which the players deviate from their optimal controls. We show that when the evader deviates from its optimal speed there are cases where there exists a new pursuer motion strategy that reduces the time to capture the evader. The shown cases where the time to capture the evader is reduced require more information about the evader’s state. Nevertheless, there are also cases in which despite the availability of new information, the pursuer must stick to the worst case strategy, otherwise it cannot capture the evader. I.
Appearance-based Motion Strategies for Object Detection Israel Becerra†, Luis M. Valentı́n-Coronado†, Rafael Murrieta-Cid † and Jean-Claude Latombe◦
"... Abstract — This paper investigates an object detection prob-lem using a mobile robot equipped with a vision sensor. The main novelty of this work is an approach that combines localization of the robot relative to an object believed to be the target and confirmation of this object’s identity. Since t ..."
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Abstract — This paper investigates an object detection prob-lem using a mobile robot equipped with a vision sensor. The main novelty of this work is an approach that combines localization of the robot relative to an object believed to be the target and confirmation of this object’s identity. Since the position of the robot relative to the candidate target is never exactly known, we model this position by a probability distribution over a set of cells forming a decomposition of the workspace around the candidate target. By performing a series of moves the robot acquires several images and runs a target detector module on each image. Its goal is not only to reach a position where the target detector can confirm the target with high confidence (as this approach would be prone to false positives). It is also to reach a position where, with high probability, the target detector will confirm with high confidence that the candidate target is actually the target. This twofold goal reduces drastically the likelihood of false positives. The target confirmation problem is modeled as a Partially-Observable Markov Decision Process (POMDP), which is solved using Stochastic Dynamic Programming (SDP). I.
Auton Robot DOI 10.1007/s10514-011-9247-y A Mixed Integer Linear Programming approach to pursuit
, 2010
"... Abstract In this paper, we address the multi pursuer version of the pursuit evasion problem in polygonal environments. By discretizing the problem, and applying a Mixed Integer Linear Programming (MILP) framework, we are able to ad-dress problems requiring so-called recontamination and also impose a ..."
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Abstract In this paper, we address the multi pursuer version of the pursuit evasion problem in polygonal environments. By discretizing the problem, and applying a Mixed Integer Linear Programming (MILP) framework, we are able to ad-dress problems requiring so-called recontamination and also impose additional constraints, such as connectivity between the pursuers. The proposed MILP formulation is less con-servative than solutions based on graph discretizations of the environment, but still somewhat more conservative than the original underlying problem. It is well known that MILPs, as well as multi pursuer pursuit evasion problems, are NP-hard. Therefore we apply an iterative Receding Horizon Control (RHC) scheme where a number of smaller MILPs are solved over shorter planning horizons. The proposed approach is implemented in Matlab/Cplex and illustrated by a number of solved examples.
†Centro de Investigación en Matemáticas, CIMAT ‡Tecnológico de Monterrey
"... Abstract — This paper is concerned with determining whether a mobile robot, called the pursuer, is up to maintaining visibility of an antagonist agent, called the evader. This problem, a variant of pursuit-evasion, has been largely studied, following a systematic treatment by increasingly relaxing a ..."
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Abstract — This paper is concerned with determining whether a mobile robot, called the pursuer, is up to maintaining visibility of an antagonist agent, called the evader. This problem, a variant of pursuit-evasion, has been largely studied, following a systematic treatment by increasingly relaxing a number of restrictions. In [8], we considered a scenario where the pursuer and the evader move at bound speed, traveling around a known, 2D environment, which contains obstacles. Then, considering that, in an attempt to escape, the evader travels the shortest path to reach a potential escape region, we provided a decision procedure that determines whether or not the pursuer is up to maintain visibility of the evader and obtained complexity measures of this surveillance task. In this paper, we prove that there are cases for which an evader may escape only if it does not travel the shortest path to an escapable region. We introduce planning strategies for the movement of the pursuer that keeps track of the evader, even if the evader chooses not to travel the shortest path to an escape region. We also present a sufficient condition for the evader to escape that does not depend on the initial positions of the players. It can be verified only using the environment. All our algorithms have been implemented and we show simulation results. I.
Search and Pursuit with Unmanned Aerial Vehicles in Road Networks
, 2013
"... Across many rescue, surveillance, and scientific applications, there exists a broad need to perform wide-area reconnaissance and terrain sur-veys, for which unmanned aerial vehicles (UAVs) are increasingly popu-lar. This thesis considers the task of using one or more UAVs to locate an object of inte ..."
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Across many rescue, surveillance, and scientific applications, there exists a broad need to perform wide-area reconnaissance and terrain sur-veys, for which unmanned aerial vehicles (UAVs) are increasingly popu-lar. This thesis considers the task of using one or more UAVs to locate an object of interest, provide continuous viewing, and rapidly re-acquire tracking should it be lost for any reason. For both the common class of small field-launched UAVs considered as well as larger UAVs, this is a difficult task due to a small available sensor field of view, uncertain estimates of UAV pose, and limited ma-neuverability relative to the scale of the environment, requiring constant processing of observations and recomputation of flight paths or sensor aiming to best find the object or keep it in view. Existing strategies for accomplishing this provide poor estimates of the object’s location and rely on grossly heuristic or computationally intensive trajectory genera-
Editorial Manager(tm) for Journal of Autonomous Agents and Multi-Agent Systems Manuscript Draft Manuscript Number: Title: Hierarchical Visibility for Guaranteed Search in Large-Scale Outdoor Terrain Article Type: Manuscript
"... To search for moving targets in a large area is a challenging task that is relevant in several problem domains, such as capturing an invader in a camp, guarding security facilities, and searching for victims in large-scale search and rescue scenarios. The guaranteed search problem is to coordinate t ..."
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To search for moving targets in a large area is a challenging task that is relevant in several problem domains, such as capturing an invader in a camp, guarding security facilities, and searching for victims in large-scale search and rescue scenarios. The guaranteed search problem is to coordinate the search of a team of agents in a way that all targets are guaranteed to be found. In this paper we present a self-contained solution to this problem in three-dimensional real-world domains represented by digital elevation models (DEMs). We introduce hierarchical sampling on DEMs for selecting strategical valuable locations from which larger parts of the map are visible. These locations are utilized to form a search graph from which search schedules are deduced, and agent paths that are directly executable in the terrain, are computed. Presented experimental results indicate that the proposed method leads to schedules requiring a significantly low number of agents for the search. The practical feasibility of our approach has been validated during a field experiment at the Gascola robot training site, where teams of humans equipped with IPads successfully searched for adversarial and omniscient evaders.
