A soft, mobile, autonomous robot to develop skills through play in autistic children

Robots have been used for many years in therapeutic activities with people with Autism Spectrum Disorder. However, most robots presented in the literature have limited or no mobility, are made of rigid materials, or are too expensive for many care centers. We share the choices and the design rationale of the latest version of a soft, mobile, low-cost, autonomous robot that has successfully been used for 3 years in a care center for activities that include both free play and structured games. Moreover, the kind of activities that can be performed with this robot, and the feedback obtained from therapists about its application are reported.

Coverage Motion Planning Using Graph in Forest Environment in Field Robot

This paper addresses the problem of using a mobile, autonomous robot to manage a forest whose trees are destined for eventual harvesting. We have been focussing a eliminate weeding operation because it is one of the hard work in the forestry works. This research proposing the computation of trajectory capable of traversing in the entire forest. The method is based on a graph whose vertices are trees located in the forest. Trees located in the forest will be treated as vertices in a graph. In the first, the initial graph is made with considering the safety of the robot. Next, editing the initial graph to be Eulerian, and finally, the Hamiltonian circuit is obtained which could be used for trajectory. By our proposed method, the trajectory of which feasible route for traversing of the entire forest would be obtained. In the experiment, we show the result of the method applying to actual artificial forest.

Mobile Ressourcen im dynamischen Produktionsumfeld*/Scheduling of mobile autonomous robot systems

Durch die im Rahmen der Industrie 4.0 forcierte Entwicklung zu einer dynamischen, wandlungsfähigen und flexiblen Produktion ergeben sich vor allem für die Produktionsplanung und -steuerung (PPS) neue Herausforderungen. Neben einem robusten Produktionsablauf und dynamischen Einflüssen müssen in Zukunft neue Ressourcen bei der Auftragsplanung berücksichtigt werden. Die Einplanung mobiler Robotersysteme ruft zusätzliche Einflussfaktoren hervor, die PPS-seitig bewerkstelligt werden müssen.   The development towards dynamic, versatile and flexible production systems in the context of Industry 4.0 creates new challenges for production planning and control (PPC). Next to a robust production process and dynamic influences, new resources have to be taken into account in the future. The scheduling of mobile autonomous robot systems is an additional influencing factor that has to be considered by PPC systems.

Robot Navigation in Forest Management

This paper addresses the problem of using a mobile, autonomous robot to manage a forest whose trees are destined for eventual harvesting. “Manage” in this context means periodical weeding between all the trees in the forest. We have constructed a robotic system enabling an autonomous robot to move between the trees without damaging them and to cut the weeds as it traverses the forest. This was accomplished by 1) computing a trajectory for the robot in advance of its entrance into the forest, and 2) developing a program and equipping the robot with the instruments needed to follow the trajectory. Computation of a trajectory in a forest is facilitated by treating the trees as vertices in a graph. Current, laser-based instruments make it possible to identify individual trees and compute distances between them. With this information a forest can be represented as a weighted graph. This graph can then be modified systematically in a way that allows for computing a Hamiltonian circuit that passes between each pair of trees. This representation is an instance of the well known Travelling Salesman Problem. The theory was put into practice in an experimental forest located at the Kyushu Institute of Technology. Our robot “SOMA,” built on an ATV platform, was able to follow a part of the trajectory computed for this small forest, thus demonstrating the feasibility of forest maintenance by an autonomous, labor saving robot.

The Pransky interview: Aldo Zini, President and CEO of Aethon, Inc.

Purpose – The following paper is a “Q & A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry engineer-turned successful business leader, regarding the commercialization and challenges of bringing technological inventions to market while overseeing a company. This paper aims to discuss these issues. Design/methodology/approach – The interviewee is Aldo Zini, President and CEO of Aethon, Inc., a robotics and software company that has developed an innovative automated platform to improve internal supply logistics. In this interview, Zini shares some of the technical and business details that have led up to the latest version of Aethon’s core product, the TUG, a mobile autonomous robot with more than 450 installs worldwide. Findings – Zini received a BS in Industrial Engineering from the University of Pittsburgh and a master’s in Public Management (Health Systems IT) from Carnegie Mellon University. While obtaining his BS degree, Zini did an internship in hospital consulting and became immediately interested in healthcare automation as a way to solve hospital inefficiencies. Zini went on to become the Vice President of Sales and Marketing for Automated Healthcare, which developed the first robotic medication dispensing system for hospitals (ROBOT-Rx) and was acquired by McKesson for $67 million. Before joining and investing in Aethon, Zini was Senior Vice President of sales and marketing for TechRx, one of the largest providers of software solutions to the pharmacy industry, which was sold to NDC Corporation for over $200 million. Originality/value – Zini has been leading the technology revolution in hospital automation for more than 25 years. His contributions to technology-driven companies have led to acquisitions worth more than a quarter of a billion dollars. Zini owns several patents in medication-dispensing technology, and is credited with the development of key methodologies in quantifying the value proposition for several technology platforms deployed in hundreds of hospitals across the country.