Design and walking analysis of proposed four-legged glass cleaning robot

In this study, a legged and wheeled robot model was proposed for cleaning the glass of greenhouses. The robot has four wheels and four legs, each with three degrees of freedom (DOF). The design, kinematic analysis and simulation of the robot was carried out. Glass greenhouses are created by placing glass sheets on T-shaped iron bars arranged in parallel at certain intervals. The robot performs the glass cleaning task by performing two different movements on greenhouse roof. As a first movement, the robot moves like a train moving on the rail on iron bars with wheels, cleaning the glass as it travels. After cleaning the glasses placed between two iron bars along a column, as second movement, the robot passes the next column using legs. These two movements continue until the entire roof of the greenhouse is cleaned. Kinematic analysis of this robot, which is designed with mechanical properties that can make these movements, has been made. Walking simulation of the robot was carried out according to the kinematic analysis. The simulation results showed that this proposed robot can be used to clean glass on the greenhouse roof

Mobile Manipulation for the KUKA youBot Platform

This paper details the implementation of object manipulation and navigation capabilities for the KUKA youBot platform. Our system builds upon existing approaches taken from other robot platforms and the open source Robot Operating System, and extends these capabilities to the youBot, resulting in a system that can detect objects in its environment, navigate to them autonomously, and both pick up and place the objects with a simple user interface. This project is part of the larger Robot Autonomy and Interactive Learning Lab project to provide web-based control of the youBot to public users

Path planning for robotic truss assembly

A new Potential Fields approach to the robotic path planning problem is proposed and implemented. Our approach, which is based on one originally proposed by Munger, computes an incremental joint vector based upon attraction to a goal and repulsion from obstacles. By repetitively adding and computing these 'steps', it is hoped (but not guaranteed) that the robot will reach its goal. An attractive force exerted by the goal is found by solving for the the minimum norm solution to the linear Jacobian equation. A repulsive force between obstacles and the robot's links is used to avoid collisions. Its magnitude is inversely proportional to the distance. Together, these forces make the goal the global minimum potential point, but local minima can stop the robot from ever reaching that point. Our approach improves on a basic, potential field paradigm developed by Munger by using an active, adaptive field - what we will call a 'flexible' potential field. Active fields are stronger when objects move towards one another and weaker when they move apart. An adaptive field's strength is individually tailored to be just strong enough to avoid any collision. In addition to the local planner, a global planning algorithm helps the planner to avoid local field minima by providing subgoals. These subgoals are based on the obstacles which caused the local planner to fail. A best-first search algorithm A* is used for graph search

Robot manipulation in human environments

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (p. 211-228).Human environments present special challenges for robot manipulation. They are often dynamic, difficult to predict, and beyond the control of a robot engineer. Fortunately, many characteristics of these settings can be used to a robot's advantage. Human environments are typically populated by people, and a robot can rely on the guidance and assistance of a human collaborator. Everyday objects exhibit common, task-relevant features that reduce the cognitive load required for the object's use. Many tasks can be achieved through the detection and control of these sparse perceptual features. And finally, a robot is more than a passive observer of the world. It can use its body to reduce its perceptual uncertainty about the world. In this thesis we present advances in robot manipulation that address the unique challenges of human environments. We describe the design of a humanoid robot named Domo, develop methods that allow Domo to assist a person in everyday tasks, and discuss general strategies for building robots that work alongside people in their homes and workplaces.by Aaron Ladd Edsinger.Ph.D

Automation and robotics for the Space Exploration Initiative: Results from Project Outreach

A total of 52 submissions were received in the Automation and Robotics (A&R) area during Project Outreach. About half of the submissions (24) contained concepts that were judged to have high utility for the Space Exploration Initiative (SEI) and were analyzed further by the robotics panel. These 24 submissions are analyzed here. Three types of robots were proposed in the high scoring submissions: structured task robots (STRs), teleoperated robots (TORs), and surface exploration robots. Several advanced TOR control interface technologies were proposed in the submissions. Many A&R concepts or potential standards were presented or alluded to by the submitters, but few specific technologies or systems were suggested

Proceedings of the NASA Conference on Space Telerobotics, volume 5

Papers presented at the NASA Conference on Space Telerobotics are compiled. The theme of the conference was man-machine collaboration in space. The conference provided a forum for researchers and engineers to exchange ideas on the research and development required for the application of telerobotics technology to the space systems planned for the 1990's and beyond. Volume 5 contains papers related to the following subject areas: robot arm modeling and control, special topics in telerobotics, telerobotic space operations, manipulator control, flight experiment concepts, manipulator coordination, issues in artificial intelligence systems, and research activities at the Johnson Space Center

Path planning and obstacle avoidance for a robot with large degree of redundancy

An algorithm to allow a redundant robot to avoid obstacles in its workspace is proposed. The task of path planning is formulated as a sequence of nonlinear programming problems. For each problem, the objective is to minimize the distance between the current location of the end-effector and some intermediate point along a desired path. Two penalties are added to the objective function to ensure that the robot is not colliding with an obstacle and that its links are intersecting one another. Inequality constraints describing the mechanical stops and limiting values for joint movements are incorporated. Obstacles are represented as polygons, which are composed of series of connecting line segments. Successive quadratic programming algorithm is used to solve the path planning problem. To save computation time, the algorithm activates the joints that are closer to the end effector. If activations of those joints cannot satisfactory complete the task, other joints will be sequentially mobilized until the desired path is reached. The proposed method is demonstrated especially efficient when the degrees of freedom are large

Indoor Navigation and Manipulation using a Segway RMP

This project dealt with a Segway RMP, utilizing it in an assistive-technology manner, encompassing navigation and manipulation aspects of robotics. First, background research was conducted to develop a blueprint for the robot. The hardware, software, and configuration of the RMP was updated, and a robotic arm was designed to extend the RMP’s capabilities. The robot was programmed to accomplish autonomous multi-floor navigation through the use of the navigation stack in ROS, image detection, and a GUI. The robot can navigate through the hallways of the building utilizing the elevator. The robotic arm was designed to accomplish tasks such as pressing a button and picking an object up off of a table. The Segway RMP is designed to be utilized and expanded upon as a robotics research platform

Hand-Gesture Based Programming of Industrial Robot Manipulators

Nowadays, industrial robot manipulators and manufacturing processes are associated as never before. Robot manipulators execute repetitive tasks with increased accuracy and speed, features necessary for industries with needs for manufacturing of products in large quantities by reducing the production time. Although robot manipulators have a significant role for the enhancement of productivity within industries, the programming process of the robot manipulators is an important drawback. Traditional programming methodologies requires robot programming experts and are time consuming. This thesis work aims to develop an application for programming industrial robot manipulators excluding the need of traditional programing methodologies exploiting the intuitiveness of humans’ hands’ gestures. The development of input devices for intuitive Human-Machine Interactions provides the possibility to capture such gestures. Hence, the need of the need of robot manipulator programming experts can be replaced by task experts. In addition, the integration of intuitive means of interaction can reduce be also reduced. The components to capture the hands’ operators’ gestures are a data glove and a precise hand-tracking device. The robot manipulator imitates the motion that human operator performs with the hand, in terms of position. Inverse kinematics are applied to enhance the programming of robot manipulators in-dependently of their structure and manufacturer and researching the possibility for optimizing the programmed robot paths. Finally, a Human-Machine Interface contributes in the programming process by offering important information for the programming process and the status of the integrated components