Whole-Body MPC for a Dynamically Stable Mobile Manipulator

Autonomous mobile manipulation offers a dual advantage of mobility provided by a mobile platform and dexterity afforded by the manipulator. In this paper, we present a whole-body optimal control framework to jointly solve the problems of manipulation, balancing and interaction as one optimization problem for an inherently unstable robot. The optimization is performed using a Model Predictive Control (MPC) approach; the optimal control problem is transcribed at the end-effector space, treating the position and orientation tasks in the MPC planner, and skillfully planning for end-effector contact forces. The proposed formulation evaluates how the control decisions aimed at end-effector tracking and environment interaction will affect the balance of the system in the future. We showcase the advantages of the proposed MPC approach on the example of a ball-balancing robot with a robotic manipulator and validate our controller in hardware experiments for tasks such as end-effector pose tracking and door opening

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

A long-term study of educational robotics and achievement in math and science

In recent years, educational robotics has become a popular tool in STEM programs, such as afterschool clubs, and summer camps, as well as classrooms. However, the research on the benefits of robotics have shown mixed results. In addition, many of the studies lack strong controls and focus on short-term effects, while the programs they investigate have few contact hours and do not have a consistent curriculum. This situation indicates that more research is needed. This work focuses on a public high school in Texas with a year-long robotics class. The first part examines a set of students who enrolled in the robotics class in the 9th or 10th grade, and a comparison group of students who did not enroll in robotics. The robotics and comparison groups were matched on 8th grade standardized math test scores, and demographic factors. Using multiple linear regression and logistic regression, I found that robotics enrollment was not a significant predictor for 11th grade math standardized test scores, or high school enrollment in Physics 1, Physics 2, or Calculus classes. The second part examines a series of video recordings of student teams in the robotics class working on a capstone project. Using grounded theory, I coded and analyzed recordings of two of the teams, focusing on the math and science discussions between the students and the contexts in which the math and science occur. Three themes emerged from the data. First, students use math/science more frequently to identify and fix problems than in their initial design. Second, students use math/science at a conceptual level and do not perform math calculations. Last, students have a “good enough” attitude and do not prioritize precision. These results may help explain the lack of effect robotics have on math test scores.Science, Technology, Engineering, and Mathematics Educatio

Making Racing Fun Through Player Modeling and Track Evolution

This paper addresses the problem of automatically constructing tracks tailor-made to maximize the enjoyment of individual players in a simple car racing game. To this end, some approaches to player modeling are investigated, and a method of using evolutionary algorithms to construct racing tracks is presented. A simple player-dependent metric of entertainment is proposed and used as the fitness function when evolving tracks. We conclude that accurate player modeling poses some significant challenges, but track evolution works well given the right track representation

VIPLE Extensions in Robotic Simulation, Quadrotor Control Platform, and Machine Learning for Multirotor Activity Recognition

abstract: Machine learning tutorials often employ an application and runtime specific solution for a given problem in which users are expected to have a broad understanding of data analysis and software programming. This thesis focuses on designing and implementing a new, hands-on approach to teaching machine learning by streamlining the process of generating Inertial Movement Unit (IMU) data from multirotor flight sessions, training a linear classifier, and applying said classifier to solve Multi-rotor Activity Recognition (MAR) problems in an online lab setting. MAR labs leverage cloud computing and data storage technologies to host a versatile environment capable of logging, orchestrating, and visualizing the solution for an MAR problem through a user interface. MAR labs extends Arizona State University’s Visual IoT/Robotics Programming Language Environment (VIPLE) as a control platform for multi-rotors used in data collection. VIPLE is a platform developed for teaching computational thinking, visual programming, Internet of Things (IoT) and robotics application development. As a part of this education platform, this work also develops a 3D simulator capable of simulating the programmable behaviors of a robot within a maze environment and builds a physical quadrotor for use in MAR lab experiments.Dissertation/ThesisMasters Thesis Computer Science 201

A comparison between a two feedback control loop and a reinforcement learning algorithm for compliant low-cost series elastic actuators

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Nonprehensile Manipulation of Deformable Objects: Achievements and Perspectives from the RoDyMan Project

The goal of this work is to disseminate the results achieved so far within the RODYMAN project related to planning and control strategies for robotic nonprehensile manipulation. The project aims at advancing the state of the art of nonprehensile dynamic manipulation of rigid and deformable objects to future enhance the possibility of employing robots in anthropic environments. The final demonstrator of the RODYMAN project will be an autonomous pizza maker. This article is a milestone to highlight the lessons learned so far and pave the way towards future research directions and critical discussions

Service Prototyping Lab Report - 2016 (Y1)

The annual activity report of the Service Prototyping Lab at Zurich University of Applied Sciences. Research trends and initiatives, research projects, transfer to education and local industry, academic community involvement, qualification and scientific development over the period of one year are among the covered topics

Broadskilling to Prepare Students for Future Work

Education professionals are concerned about quality of the education our youth receive. Corporations are concerned about having a prepared, skilled workforce as we face a sweeping digital transformation. Impact metrics vary, but there are clear themes about concerns of the emerging generation of workers (“will a robot take my job?”) and skills gaps. While corporate HR leans in on innovative recruiting, “upskilling” and “reskilling” initiatives, the opportunity for students is “Broadskilling” (i.e. career awareness, entrepreneurship, soft skills, adaptability, learning to learn, and befriending technology). Let’s engage in a practical discussion based on current data and share our experiences and stories