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Dive into the research topics where Howie Choset is active.

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Featured researches published by Howie Choset.


Annals of Mathematics and Artificial Intelligence | 2001

Coverage for robotics – A survey of recent results

Howie Choset

This paper surveys recent results in coverage path planning, a new path planning approach that determines a path for a robot to pass over all points in its free space. Unlike conventional point-to-point path planning, coverage path planning enables applications such as robotic de-mining, snow removal, lawn mowing, car-body painting, machine milling, etc. This paper will focus on coverage path planning algorithms for mobile robots constrained to operate in the plane. These algorithms can be classified as either heuristic or complete. It is our conjecture that most complete algorithms use an exact cellular decomposition, either explicitly or implicitly, to achieve coverage. Therefore, this paper organizes the coverage algorithms into four categories: heuristic, approximate, partial-approximate and exact cellular decompositions. The final section describes some provably complete multi-robot coverage algorithms.


international conference on robotics and automation | 2001

Topological simultaneous localization and mapping (SLAM): toward exact localization without explicit localization

Howie Choset; Keiji Nagatani

This paper presents a new method for simultaneous localization and mapping that exploits the topology of the robots free space to localize the robot on a partially constructed map. The topology of the environment is encoded in a topological map; the particular topological map used in this paper is the generalized Voronoi graph (GVG), which also encodes some metric information about the robots environment, as well. In this paper, we present the low-level control laws that generate the GVG edges and nodes, thereby allowing for exploration of an unknown space. With these prescribed control laws, the GVG can be viewed as an arbitrator for a hybrid control system that determines when to invoke a particular low-level controller from a set of controllers all working toward the high-level capability of mobile robot exploration. The main contribution, however, is using the graph structure of the GVG, via a graph matching process, to localize the robot. Experimental results verify the described work.


Autonomous Robots | 2000

Coverage of Known Spaces: The Boustrophedon Cellular Decomposition

Howie Choset

Coverage path planning is the determination of a path that a robot must take in order to pass over each point in an environment. Applications include de-mining, floor scrubbing, and inspection. We developed the boustrophedon cellular decomposition, which is an exact cellular decomposition approach, for the purposes of coverage. Essentially, the boustrophedon decomposition is a generalization of the trapezoidal decomposition that could allow for non-polygonalobstacles, but also has the side effect of having more “efficient” coverage paths than the trapezoidal decomposition. Each cell in the boustrophedon decomposition is covered with simple back and forth motions. Once each cell is covered, then the entire environment is covered. Therefore, coverage is reduced to finding an exhaustive path through a graph which represents the adjacency relationships of the cells in the boustrophedon decomposition. This approach is provably complete and experiments on a mobile robot validate this approach.


The International Journal of Robotics Research | 2000

Sensor-Based Exploration: The Hierarchical Generalized Voronoi Graph

Howie Choset; Joel W. Burdick

The hierarchical generalized Voronoi graph (HGVG) is a new roadmap developed for sensor-based exploration in unknown environments. This paper defines the HGVG structure: a robot can plan a path between two locations in its work space or configuration space by simply planning a path onto the HGVG, then along the HGVG, and finally from the HGVG to the goal. Since the bulk of the path planning occurs on the one-dimensional HGVG, motion planning in arbitrary dimensioned spaces is virtually reduced to a one-dimensional search problem. A bulk of this paper is dedicated to ensuring the HGVG is sufficient for motion planning by demonstrating the HGVG (with its links) is an arc-wise connected structure. All of the proofs in this paper that lead toward the connectivity result focus on a large subset of spaces in R3, but wherever possible, results are derived in Rm. In fact, under a strict set of conditions, the HGVG (the GVG by itself) is indeed connected, and hence sufficient for motion planning. The chief advantage of the HGVG is that it possesses an incremental construction procedure, described in a companion paper, that constructs the HGVG using only line-of-sight sensor data. Once the robot constructs the HGVG, it has effectively explored the environment, because it can then use the HGVG to plan a path between two arbitrary configurations.


international conference on robotics and automation | 2004

Limited communication, multi-robot team based coverage

Ioannis M. Rekleitis; Vincent Lee-Shue; Ai Peng New; Howie Choset

This paper presents an algorithm for the complete coverage of free space by a team of mobile robots. Our approach is based on a single robot coverage algorithm, which divides the target two-dimensional space into regions called cells, each of which can be covered with simple back-and-forth motions; the decomposition of free space in a collection of such cells is known as Boustrophedon decomposition. Single robot coverage is achieved by ensuring that the robot visits every cell. The new multi-robot coverage algorithm uses the same planar cell-based decomposition as the single robot approach, but provides extensions to handle how teams of robots cover a single cell and how teams are allocated among cells. This method allows planning to occur in a two-dimensional configuration space for a team of N robots. The robots operate under the restriction that communication between two robots is available only when they are within line of sight of each other.


The International Journal of Robotics Research | 2003

Path Planning for Robotic Demining: Robust Sensor-Based Coverage of Unstructured Environments and Probabilistic Methods

Ercan U. Acar; Howie Choset; Yangang Zhang; Mark J. Schervish

Demining and unexploded ordnance (UXO) clearance are extremely tedious and dangerous tasks. The use of robots bypasses the hazards and potentially increases the efficiency of both tasks. A first crucial step towards robotic mine/UXO clearance is to locate all the targets. This requires a path planner that generates a path to pass a detector over all points of a mine/UXO field, i.e., a planner that is complete.The current state of the art in path planning for mine/UXO clearance is to move a robot randomly or use simple heuristics. These methods do not possess completeness guarantees which are vital for locating all of the mines/UXOs. Using such random approaches is akin to intentionally using imperfect detectors. In this paper, we first overview our prior complete coverage algorithm and compare it with randomized approaches. In addition to the provable guarantees, we demonstrate that complete coverage achieves coverage in shorter time than random coverage. We also show that the use of complete approaches enables the creation of a filter to reject bad sensor readings, which is necessary for successful deployment of robots. We propose a new approach to handle sensor uncertainty that uses geometrical and topological features rather than sensor uncertainty models. We have verified our results by performing experiments in unstructured indoor environments. Finally, for scenarios where some a priori information about a minefield is available, we expedite the demining process by introducing a probabilistic method so that a demining robot does not have to perform exhaustive coverage.


intelligent robots and systems | 2003

A mobile hyper redundant mechanism for search and rescue tasks

Alon Wolf; H.B. Brown; R. Casciola; Albert Costa; Michael Schwerin; E. Shamas; Howie Choset

In this work we introduce a new concept of a search and rescue robotic system that is composed of an elephant trunk-like robot mounted on a mobile base. This system is capable not only of inspecting areas reachable by the mobile base but also to inspect unreachable areas such as small cracks, and pipes, using the camera mounted on its elephant trunk robot. In the report we describe the mechanical structure of the elephant trunk robot, the kinematic analysis of the structure, the robot control, and its human interface systems.


intelligent robots and systems | 2007

Design of a modular snake robot

Cornell Wright; Aaron M. Johnson; Aaron Peck; Zachary McCord; Allison Naaktgeboren; Philip Gianfortoni; Manuel Gonzalez-Rivero; Ross L. Hatton; Howie Choset

Many factors such as size, power, and weight constrain the design of modular snake robots. Meeting these constraints requires implementing a complex mechanical and electrical architecture. Here we present our solution, which involves the construction of sixteen aluminum modules and creation of the Super Servo, a modified hobby servo. To create the Super Servo, we have replaced the electronics in a hobby servo, adding such components as sensors to monitor current and temperature, a communications bus, and a programmable microcontroller. Any robust solution must also protect components from hazardous environments such as sand and brush. To resolve this problem we insert the robots into skins that cover their surface. Functions such as climbing the inside and outside of a pipe add a new dimension of interaction. Thus we attach a compliant, high-friction material to every module, which assists in tasks that require gripping. This combination of the mechanical and electrical architectures results in a robust and versatile robot.


The International Journal of Robotics Research | 2000

Sensor-Based Exploration: Incremental Construction of the Hierarchical Generalized Voronoi Graph

Howie Choset; Sean Walker; Kunnayut Eiamsa-Ard; Joel W. Burdick

This paper prescribes an incremental procedure to construct roadmaps of unknown environments. Recall that a roadmap is a geometric structure that a robot uses to plan a path between two points in an environment. If the robot knows the roadmap, then it knows the environment. Likewise, if the robot constructs the roadmap, then it has effectively explored the environment. This paper focuses on the hierarchical generalized Voronoi graph (HGVG), detailed in the companion paper in this issue. The incremental construction procedure of the HGVG requires only local distance sensor measurements, and therefore the method can be used as a basis for sensor-based planning algorithms. Simulations and experiments using a mobile robot with ultrasonic sensors verify this approach.


intelligent robots and systems | 2003

Composition of local potential functions for global robot control and navigation

David C. Conner; Alfred A. Rizzi; Howie Choset

This paper develops a method of composing simple control policies, applicable over a limited region in a dynamical systems free space, such that the resulting composition completely solves the navigation and control problem for the given system operating in a constrained environment. The resulting control policy deployment induces a global control policy that brings the system to the goal, provided that there is a single connected component of the free space containing both the start and goal configurations. In this paper, control policies for both kinematic and simple dynamical systems are developed. This work assumes that the initial velocities are somewhat aligned with the desired velocity vector field. We conclude by offering an outline of an approach for accommodating arbitrary dynamical constraints and initial conditions.

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Chaohui Gong

Carnegie Mellon University

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George Kantor

Carnegie Mellon University

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Daniel I. Goldman

Georgia Institute of Technology

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Amir Degani

Technion – Israel Institute of Technology

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Brett Zubiate

University of Pittsburgh

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Ercan U. Acar

Carnegie Mellon University

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Stephen Tully

Carnegie Mellon University

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David Rollinson

Carnegie Mellon University

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