Browsing by Subject "Motion Planning"
Now showing items 1-20 of 24
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(2016-02-15)Multiple small autonomous or unmanned aerial and ground vehicles are being used together with stationary sensing devices for a wide variety of data gathering, monitoring and surveillance applications in military, civilian, ...
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(2020-04-27)Motion planning is an important problem in robotics which addresses the question of how to transition an actor between states in an environment subject to obstacles, kinematic, and other constraints. Exact motion planning ...
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(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 ...
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When attempting to plan for an interaction between two robots there are many factors that compound its complexity, including the number of joints each robot has, causes for collision, power usage, placement of the end ...
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(2012-02-14)Mobile robots are used on many areas and its demand on extreme terrain, hazardous area, or life-threatening place is increasing to reduce the loss of life. A good decision making capability is essential for successful ...
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(2020-04-02)Over the past few decades, researchers have worked towards developing autonomous systems that can be used in everyday transportation, and with the emergence of new sensor, hardware, and software technologies, the goal of ...
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(2014-05-07)This dissertation addresses the problem of stochastic optimal control with imperfect measurements. The main application of interest is robot motion planning under uncertainty. In the presence of process uncertainty and ...
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(2019-04-10)Geometric approximation methods are a preferred solution to handle complexities (such as a large volume or complex features such as concavities) in geometric objects or environments containing them. Complexities often pose ...
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(2019-08-14)This work describes a framework for multi-robot problems that require or utilize interactions between robots. Solutions consider interactions on a motion planning level to determine the feasibility and cost of the multi-robot ...
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(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 ...
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(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 ...
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(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 ...
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(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 ...
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Motion Planning algorithms have been studied in many applications, such as network design and robotic motions. However, in the field of Robotics, in some settings the motion might be limited by a cable, preventing the robot ...
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(Texas A&M University, 2006-10-30)A methodology is presented in this work for intelligent motion planning in an uncertain environment using a non-local sensor, like a radar sensor, that allows the sensing of the environment non-locally. This methodology ...
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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 ...
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(2013-08-27)The motion planning problem in robotics is to find a valid sequence of motions taking some movable object from a start configuration to a goal configuration in an environment. Sampling-based path planners are very popular ...
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(2019-10-18)Decision making under uncertainty is an important problem in engineering that is traditionally approached differently in each of the Stochastic optimal control, Reinforcement learning and Motion planning disciplines. One ...
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(2023-01-19)Autonomous vehicles(AVs) have the potential to revolutionize how we ultimately perceive modern transportation. Many current car models already feature advanced driver-assist systems (ADAS), such as adaptive cruise control ...
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(2019-08-28)This research aims at developing path and motion planning algorithms for a tethered Unmanned Aerial Vehicle (UAV) to visually assist a teleoperated primary robot in unstructured or confined environments. The emerging state ...