Dynamic Obstacle Avoidance for Omnidirectional Mobile Manipulators

The last decade witnessed an unprecedented spread of robotics. The production paradigm of Industry 4.0 and 5.0 yielded collaborative robots in production lines of all sizes. Also, the robots started leaving the industrial scenario to play a leading role in the field of personal assistance. These environments share a common challenge, i.e. the safety of people working and/or living around the robots. Collision avoidance control techniques are essential to improve such aspect, by preventing impacts that can occur between the robot and humans or objects. The paper extends algorithms already developed by the authors for robotic arms to the case of mobile manipulators. The control strategy, which has been refined in the contribution of the robot bodies, has then been tested in two simulated case studies involving an industrial mobile robot and the custom service robot Paquitop, developed at Politecnico di Torino

Fostering Resilient Aging with a Self-efficacy and Independence Enabling Robot (FRASIER)

With the percentage of the elderly population rapidly increasing as the Baby Boomer generation reaches retirement, the demand for assistive care will soon override the supply of caregivers available. Additionally, as most individuals age, the number of age-related limitations preventing them from completing everyday tasks independently may increase. Through FRASIER (Fostering Resilient Aging with a Self-efficacy and Independence Enabling Robot), the project team developed an assistive robot with a goal of providing a solution to this challenge

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

NASA space station automation: AI-based technology review. Executive summary

Research and Development projects in automation technology for the Space Station are described. Artificial Intelligence (AI) based technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics

Robotic assisted deep brain stimulation neurosurgery: first steps on system development

The advantages of Deep Brain Stimulation (DBS) lead to an increasing number of stereotactic DBS surgeries, which are extensive procedures that require extreme precision and steadiness of tool handling. Robotic manipulators known for their consistency, movement precision and steadiness have the potential to be remarkable tools to assist the neurosurgeons and can refine the quality/working conditions, while improving surgery outcome. Currently, robotic systems for stereotactic neurosurgeries with simple/pragmatic low budget solutions that fulfil the surgeons' needs are not yet available. Thus, we have been asked to develop such robotic system. In this paper we present our first steps toward such endeavour. Specifically, we implemented a simulation environment for robotic assisted DBS neurosurgery that allows emulating several hardware setups within the operating room, and to test and assess their performance. The simulator is useful not only as tool for developing specialized control applications, but also for training clinicians. First results support the viability of the sought solution and open way to future developments.This work has been partially financed by projects FP7 Marie Curie ITN - NETT (project no 289146), FCT FCOMP-01-0124-FEDER-022674 and Pest-C/MATUI0013/2011 (FCT grant ref. UMINHO/BIC/8/2012)

Autonomous UAS-Based Agriculture Applications: General Overview and Relevant European Case Studies

Emerging precision agriculture techniques rely on the frequent collection of high-quality data which can be acquired efficiently by unmanned aerial systems (UAS). The main obstacle for wider adoption of this technology is related to UAS operational costs. The path forward requires a high degree of autonomy and integration of the UAS and other cyber physical systems on the farm into a common Farm Management System (FMS) to facilitate the use of big data and artificial intelligence (AI) techniques for decision support. Such a solution has been implemented in the EU project AFarCloud (Aggregated Farming in the Cloud). The regulation of UAS operations is another important factor that impacts the adoption rate of agricultural UAS. An analysis of the new European UAS regulations relevant for autonomous operation is included. Autonomous UAS operation through the AFarCloud FMS solution has been demonstrated at several test farms in multiple European countries. Novel applications have been developed, such as the retrieval of data from remote field sensors using UAS and in situ measurements using dedicated UAS payloads designed for physical contact with the environment. The main findings include that (1) autonomous UAS operation in the agricultural sector is feasible once the regulations allow this; (2) the UAS should be integrated with the FMS and include autonomous data processing and charging functionality to offer a practical solution; and (3) several applications beyond just asset monitoring are relevant for the UAS and will help to justify the cost of this equipment.publishedVersio