Browsing by Author "McLurkin, James D."

Now showing 1 - 4 of 4
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    Distributed Space Coverage for Exploration, Localization, and Navigation in Unknown Environments
    (2015-04-22) Lee, Seoung Kyou; McLurkin, James D.; Kavraki, Lydia; Hicks, Illya; Fekete, Sándor
    Many tasks, such as search and rescue, exploration and mapping, security and surveil- lance are suited for mobile robots. These tasks require the population to spread out over a large environment, where the sensing and communicating capacity of an individual robot might be too small to cover the entire environment. This thesis presents approaches for cooperative coverage tasks by large populations of robots to overcome the limitation of a single robot. Not only can a multi-robot system accomplish the coverage task far more efficiently than an individual robot, but also it is more reliable against individual hardware failure. This thesis investigates two different scenarios with respect to distributed multi-robot space coverage in an unknown environment: First, I consider the space coverage in un- bounded environments. This scenario takes care of robots searching or monitoring in an unlimited region, such as a forest or submarine sea floor. For efficient scanning, robots need to spread out sufficiently to cover a large area. At the same time, they have to be close to their neighbors to prevent network disconnection. In order to fulfill both requirements simultaneously, I present a cohesive configuration controller by combining existing flock- ing strategies with a boundary force algorithm and network sensing and mode switching method. By doing so, robots form a convex and cohesive configuration without any dis- connection. Moreover, they maintain this final configuration even while moving. Secondly, I study space coverage problem in bounded environments that pursues to build a robotic sensor network. In this scenario, I present an algorithm to construct a triangulation using multiple low-cost robots. The resulting triangulation approximately maps the geometric characteristics of its surrounding environment and produces a physical data structure that stores triangle information distributively. This physical data structure provides auxiliary data to robots and lets them accomplish the application’s goal using only local communications. In this thesis, I address one simple application for patrolling and one complex application for topological Voronoi tessellation and center computation. This work provides theoretical guarantees about the algorithm performance. I also provide numerous simulation and hardware experiment results using the model of low- cost platforms to validate the feasibility of presented methods. In both scenarios, robots successfully form desired configurations without the aid of centralized infrastructures. In addition, the group of robots maintains the connectivity while running the algorithms.
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    Multi-robot behaviors with bearing-only sensors and scale-free coordinates
    (2012) Lynch, Andrew J.; McLurkin, James D.
    This thesis presents a low-cost multi-robot system for large populations of robots, a new coordinate system for the robot based on angles between robots and a series of experiments validating robot performance. The new robot platform, the r-one will serve as an educational, outreach and research platform for robotics. I consider the robot's bearing-only sensor model, where each robot is capable of measuring the bearing, but not the distance, to each of its neighbors. This work also includes behaviors demonstrating the efficiency of this approach with this bearing-only sensor model. The new local coordinate systems based on angular information is introduced as scale-free coordinate system . Each robot produces its own local scale-free coordinates to determine the relative positions of its neighbors up to an unknown scaling factor. The computation of scale-free coordinates is analyzed with hardware and simulation validation. For hardware, the scale-free algorithm is tailored to low-cost systems with limited communication bandwidth and sensor resolution. The algorithm also uses a noise sensitivity model to reduce the impact of noise on the computed scale-free coordinates. I validate the algorithm with static and dynamic motion experiments.
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    Pose Estimation With Low-Resolution Bearing-Only Sensors
    (2012) Rykowski, Joshua B.; McLurkin, James D.
    Pose estimation of neighboring robots is a key requirement for configuration control behaviors in multi-robot systems. Estimating pose is difficult without system constraints, it is even more challenging when using minimalistic sensing alongside limited bandwidth. Minimal sensing models are a well studied field in robotics and are relevant to our particular hardware platform, the r-one, which has sensors that only measure a low-resolution bearing to neighboring robots. These bearing-only sensors are simpler to design with and cheaper to deploy in large numbers. In this thesis, I focus on the r-one multi-robot system which is capable of coarsely measuring the bearing, but not the distance, to neighbors. These sensors have a angular resolution of only 22.5 degrees due to the construction of the infrared system. I develop a particle filter algorithm that allows the r-one robot to estimate the pose of a neighbor using the infrared communication system and odometry measurements. This algorithm relies on the fusion of a coarse bearing measurement and neighbor velocities and is optimized to use the smallest communications bandwidth possible. I tested this algorithm with a simulation to demonstrate its effectiveness across varying sensor setups, neighbor update periods, and number of particles.
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    Swarm Robotics: Measurement and Sorting
    (2015-04-24) Zhou, Yu; McLurkin, James D.; Kavraki, Lydia E; Chaudhuri, Swarat
    To measure is an important ability for robots to sense the environment and nearby robots. Although camera, laser, and ultrasonic provide very accurate measurements, they are expensive and not scalable for large swarm of low-cost robots. The r-one robot designed at Rice University is equipped with infrared transmitters and receivers, which are designed for remote control and are very inexpensive in mass production. They are a good solution for short-range communication, since the signal attenuates at about 1 to 2 meters with appropriate voltage. This work describes my results in using them to measure bearing, orientation, and distance between nearby robots. However, infrared receivers are not designed for this kind of use, so I present a variable transmit power approach to allow useful and efficient local geometry measurements. With the ability to measure bearing and distance, I am able to solve the problem of sorting a group of n robots in a two-dimensional space. I want to organize robots into a sorted and equally-spaced path between the robots with lowest and highest label, while maintaining a connected communication network throughout the process. I begin with a straightforward geometry-based version of sorting algorithm, and point out there are many difficulties when communication range becomes limited. Then I describe a topology-based distributed algorithm for this task. I introduce operations to break the symmetry between minimum and maximum, in order to keep time, travel distance, and communication costs low without using central control. I run a set of algorithms (leader election, tree formation, path formation, path modification, and geometric straightening) in parallel. I show that my overall approach is safe, correct, and efficient. It is robust to population changes, network connectivity changes, and sensor errors. I validate my theoretical results with simulation results. My algorithm implementation uses communication messages of fixed size and constant memory on each robot, and is a practical solution for large populations of low-cost robots.