Now showing items 1-18 of 18

    • A Novel Continuum Manipulator 

      Cochrane, Eric C (2015-09-21)
      We address the problem of controlling continuum manipulators and evaluate Reinforcement Learning to produce a control policy for a robotic platform. Our approach discretizes the state and action spaces to reduce the training ...
    • A Scalable Framework for Parallelizing Sampling-Based Motion Planning Algorithms 

      Jacobs, Samson Ade (2014-04-29)
      Motion planning is defined as the problem of finding a valid path taking a robot (or any movable object) from a given start configuration to a goal configuration in an environment. While motion planning has its roots in ...
    • Advancing Embedded and Extrinsic Solutions for Optimal Control and Efficiency of Energy Systems in Buildings 

      Bay, Christopher Joseph (2017-05-23)
      Buildings account for approximately 40% of all U.S. energy usage and carbon emissions. Reducing energy usage and improving efficiency in buildings has the potential for significant environmental and economic impacts. To ...
    • Collaborative Motion Planning 

      Denny, Jory London (2016-07-26)
      Planning motion is an essential component for any autonomous robotic system. An intelligent agent must be able to efficiently plan collision-free paths in order to move through its world. Despite its importance, this problem ...
    • Incorporating haptic features into physics-based simulation 

      Zhao, Rukai (Texas A&M University. Libraries, 2019-05)
      In our graphic lab, we have developed many physics-based animations focusing on muscles and we hope to create an interactive interface with tactile feedback so that the users can not only see those physical features but ...
    • Local Randomization in Neighbor Selection Improves PRM Roadmap Quality 

      Boyd, Bryan 1985- (2012-08-27)
      Probabilistic Roadmap Methods (PRMs) are one of the most used classes of motion planning methods. These sampling-based methods generate robot configurations (nodes) and then connect them to form a graph (roadmap) containing ...
    • Medial-Axis Biased Rapidly-Exploring Random Trees 

      Greco, Evan (2012-05-09)
      RRTs (Rapidly-Exploring Random Trees) have shown wide applications in robotics. RRTs are a type of sampling-based motion planners that expand to fill the space starting from one or more root configurations. RRTs are excellent ...
    • Metrics for sampling-based motion planning 

      Morales Aguirre, Marco Antonio (2009-05-15)
      A motion planner finds a sequence of potential motions for a robot to transit from an initial to a goal state. To deal with the intractability of this problem, a class of methods known as sampling-based planners build ...
    • Miniature Autonomous Robots for Pipeline Inspection 

      Moss, William Tyler (2016-08-24)
      Aging natural gas pipeline infrastructure is becoming an increasingly large problem in the United States. There are more than 2.4 million miles of pipelines currently in use, all of which require regular maintenance and ...
    • Motion Planning for a Tethered Mobile Robot 

      HosseiniTeshnizi, Reza (2015-08-12)
      Recently there has been surge of research in motion planning for tethered robots. In this problem a planar robot is connected via a cable of limited length to a fixed point in R2. The configuration space in this problem ...
    • Multi Degree of Freedom Hinge Joints Embedded on Tubes for Miniature Steerable Medical Devices 

      Pattanshetti, Shivanand (2017-08-01)
      With the proliferation of successful minimally invasive surgical techniques, comes the challenge of shrinking the size of surgical instruments further to facilitate use in applications such as neurosurgery, pediatric ...
    • Multi-Agent Persistent Task Performance 

      Motes, James Donald
      A method to control a system of robots to persistently perform a task while operating under a constraint such as battery life is presented. Persistently performing a task is defined as continuously executing the task without ...
    • Real-Time Classification of Road Conditions 

      Weaver, Scott M (2015-09-03)
      Common navigation algorithms like A* or D* Lite rely on costs to determine an optimal path. Costs may incorporate distance, time, or energy consumption; however, they can include anything that affects travel along a path. ...
    • Realizing Torque Controllers for Underactuated Bipedal Walking Using the Ideal Model Resolved Motion Method 

      Cousineau, Eric Andrew (2014-12-16)
      This thesis presents an application of hybrid zero dynamics to realize underactuated bipedal walking on DURUS, a testbed designed and built by SRI International. The main contribution of this work is the ideal model resolved ...
    • Robot Locomotion Controller Generation Through Human-Inspired Optimization 

      Powell, Matthew Joseph (2013-11-13)
      This thesis presents an approach to the formal design, optimization and implementation of bipedal robotic walking controllers, with experimental application on two biped platforms. Standard rigid-body modeling is used to ...
    • Sampling Based Motion Planning with Reachable Volumes 

      McMahon, Troy Anthony (2016-08-08)
      Motion planning for constrained systems is a version of the motion planning problem in which the motion of a robot is limited by constraints. For example, one can require that a humanoid robot such as a PR2 remain upright ...
    • TOGGLE PRM: A SIMULTANEOUS MAPPING OF CFREE AND COBSTACLE FOR USE IN PROBABILISTIC ROADMAP METHODS 

      Denny, Jory 1991- (2011-04-14)
      Motion planning for robotic applications is difficult. This is a widely studied problem in which the best known deterministic solution is doubly exponential in the dimensionality of the problem. A class of probabilistic ...
    • Unifying Consensus and Covariance Intersection for Efficient Distributed State Estimation over Unreliable Networks 

      Tamjidi, Amirhossein (2017-05-10)
      This thesis studies the problem of recursive distributed state estimation over unreliable networks. The main contribution is to fuse the independent and dependent information separately. Local estimators communicate directly ...