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Collision-free Motion Planning for Human-Robot Collaborative Safety under Cartesian Constraints
This thesis presents a real-time motion planning and control design of a robot arm for human-robot collaborative safety. Multiple KinectV2 depth camera are utilized to model and track dynamic obstacles (e.g. Humans and objects) inside the robot workspace. Depth images are applied to generate the point cloud of segmented objects in the environment. A K-nearest neighbor (KNN) searching algorithm is used to cluster and find the closest point from the obstacle point cloud to the robot. Then, a Kalman filter is applied to estimate the obstacle position and velocity. For the collision avoidance behavior, the repulsive force is generated for the robot end effector by calculating the minimum distance between the robot and moving obstacles. Moreover, a novel collision-free motion planning method is proposed not only to keep robot body from colliding with objects but also to preserve the execution of robot’s original task under the Cartesian constraint of the environment. Practical experiments show that the 6-DOF robot arm can effectively avoid obstacles in a constrained environment and complete the original task.
Voice Remote Control Design of a Mobile Robot Using Shared-Control Approach
Human voice provides a convenient and natural way to communicate with a service robot. It is desirable to operate a mobile robot using voice commands. However, in practice, simple voice commands are not sufficient to give continuous and safe motion of a mobile robot in a complex environment. This work studies a shared-control approach to remote control of a mobile robot. A remote control scheme for an omnidirectional mobile robot is proposed to overcome the delay-time problem of voice commands and maintain the safe motion of the robot using simple voice commands. In this work, we combine the robot autonomy and human intention by using shared-control techniques. The human and robot interactive gains are obtained by computing posterior of free-space using a Bayesian recursive algorithm. Experimental results are presented to demonstrate the effectiveness of the proposed method.
Design and Implementation of an Attitude Controller for an Octocopter Using Fuzzy+PID
The objective of this work is to design and implement attitude control for an octocopter. Octocopter is one of the Unmanned Aerial Vehicles (UAVs), which have grown fast recently, and various applications have been developed. In this work, the dynamic model of an octocopter is obtained by making the configuration similar to a quadcopter. In order to stabilize the attitude control of the octocopter, we proposed a Fuzzy+PID design of the attitude controller. Both computer simulation and real-time experiments have been carried out by using LabVIEW programming. In the simulation, we investigated the performance of the proposed Fuzzy+PID controller and tuned the controller parameters. For real-time control, NI-MyRio has been chosen to implement the controller onboard the octocopter. The practical experiments show that the proposed Fuzzy+PID controllers can handle the disturbances during flying and have robustness against certain environmental conditions. The experimental results validate the simulations and verify the effectiveness of the developed controller.
Compliant Motion Control of a Walk-Assistant Robot Based on Force and Gait Information
This thesis presents a new method to provide compliant motion of a walk assistant robot based on user status and motion intent. A laser scanner is used to detect the user's gait information and a force/torque sensor detects desired motion direction. The compliance controls will provide the walking assistance. The robot velocity is regulated by user gait information and the robot motion direction is adjusted by force/torque sensor information. These two compliant controllers allow the walking assist robot to generate passive behavior and provide walking assistance effectively.
Shared-Controller Design for an Omnidirectional Interactive Robot
It is usually difficult to remotely control of a mobile robot using only an onboard camera. The robot can easily bump into an obstacle due to limited view angle of the on-site scene. The thesis presents a shared-control architecture for effective remote control an omnidirectional mobile platform. The platform is able to move in any direction without changing robot’s heading, such that a stable camera scene is available for remote control. A user interface is designed to use smart phone/tablet to remote control the robot by the interactive touch screen. The proposed controller determines the human and robot interactive gains by computing user’s confidence factor.
CAD-Based Pose Estimation for Random Bin-Picking of Multiple Objects
In this thesis, we propose a CAD-based 6-DOF pose estimation design for random bin-picking of multiple objects using a Kinect RGB-D sensor. A voting-scheme was adopted for 6-DOF pose estimation as well as recognition of a set of 6-DOF poses of different types of objects in the bin. We combine 3D CAD model of objects with a virtual camera to generate point cloud database for pose estimation. A design based on voxel grid filter is suggested to decrease the number of 3D point cloud of object for reducing time of pose estimation. Furthermore, we use an outlier filter to filter out bad matching poses and occluded ones.
Probability-Based Pose Planning for Mobile Manipulation
In this thesis, a system is designed and experimented for efficient mobile manipulation of a dual-arm robot. Because of limited workspace of the robot arm, robot grasping may fail if the target object is outside the workspace. At the same time, navigation errors also affect the grasping as the robot needs to move toward the target object. In this thesis, we construct a graspability map to describe the possibility of successful grasping inside workspace of the robot arm and we also construct a reachability map to describe the feasibility the robot can navigate to the target. These two maps are integrated to determine the robot location for grasping the target object.
Instrument Contact Force Estimation Using a 3D Reconstruction Model
This thesis aims to develop a method to estimate contact force for minimally invasive surgery (MIS) by using image processing and 3D reconstruction modeling. In order to provide surgeons a feeling of contact force between human tissue and instrument, we develop a method to calculate tissue deformation by reconstructing 3D model and estimate force information. The force information will be feed-back to a haptic device to allow a surgeon feel contact force. In this thesis, we propose a 3D model reconstruction method to calculate tissue surface under deformation, and use the deformation data to obtain contact force near the instrument tip.
Design of Location aware Systems using ZigBee-based Intelligent Environment and Mobile Robots
A location aware system provides location information of objects, users and mobile robots from sensor nodes deployed in the intelligent environment. The information can be used to support various intelligent behaviors of a service robot in day-to-day application scenarios. This thesis presents a probability-based approach to building a location aware system. With this approach, the inconsistencies often encountered in received signal strength indicator (RSSI) measurements are handled with a minimum calibration.
Surgical Instrument Recognition and Tracking Using Endoscopic Image Sequences
The objective of this study is to design an image tracking algorithm for the endoscopic system in Minimally Invasive Surgery (MIS). The endoscopic robot autonomously adjusts its pose according to the position of the instruments in image plane, and moves the endoscope to provide a suitable field of view. A method is proposed to identify the tip of instruments without using extra artificial markers.
Mobile Manipulation and Visual Servoing Design of a Configurable Mobile Manipulator
This paper presents a mobile manipulation and visual servoing design for a configurable mobile manipulator by using a Kinect sensor. The goal of this method and design is to execute mobile manipulation tasks in dynamic environments. To achieve this goal, a mobile manipulation and visual grasping design is combined a vSLAM (visual simultaneous localization and mapping). The vSLAM method is proposed based on extended Kalman filter (EKF) and a Kinect RGBD sensor.
Interactive Emotional Brain
The goal of this study is to develop a robot (face) that can present proper emotional expression to a user in response to his/her emotional state.
The development of a robotic interactive emotional brain (IEB) can handle emotional state generation of a robot.IEB allows the robot to autonomously generate intimate and natural emotional behaviors in response to user’s emotional state. Different emotional characteristics of a robot can be designed-in an IEB.
Slope Surface Compliant Motion Control Design of a Walking Helper Robot
The goal of this study is to develop a walk-assistive system for the elderly people. The robot should comply with the user’s motion intent without using a force/torque sensor.
The gravity effect is especially considered and compensated by the force observer such that the robot posses compliance on an slope surface.
Monocular Vision-based Robot Navigation
The goal of this study is to navigate a robot autonomously using merely a monocular camera.
An image processing procedure is developed to estimate distances between the robot and obstacles based-on inverse perspective transformation (IPT) in image plane. The proposed method integrates robust feature matching with adaptive color segmentation for plane estimation and tracking to cope with variations in illumination and camera view.
An Adaptive Routing Protocol for Mobile Ad-Hoc Networks
Mobile robots can be used to collect information in an environment by using Mobile Ad-hoc Network (MANET) technology.For elderly-care, a MANET can be constructed to let the robot know the conditions of the elderly people in order to handle emergency situations in time. Due to node mobility, routing of the packet passing is an important issue in MANET. This study brings out an AODV with fuzzy system to combined signal strength and to improve the route.
Omni-directional Mobile Manipulator
Recent trend of robotic research is to enhance the robotic technology for more assistance and service to human beings. However, it is a challenge for a mobile manipulator to work in an unstructured and dynamic changing environment such in a home setting. Advanced hard and software design needs to be considered for a safe and reliable operation of a robot equipped with a manipulator. This project aims to study vision-based mobile manipulation challenges.
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