George P. Moustris

Evolution of autonomous and semi-autonomous robotic surgical systems: a review of the literature

Autonomous control of surgical robotic platforms may offer enhancements such as higher precision, intelligent manoeuvres, tissue‐damage avoidance, etc. Autonomous robotic systems in surgery are largely at the experimental level. However, they have also reached clinical application.

Fuzzy logic path tracking control for autonomous non-holonomic mobile robots: Design of System on a Chip

This paper presents a System on Chip (SoC) for the path following task of autonomous non-holonomic mobile robots. The SoC consists of a parameterized Digital Fuzzy Logic Controller (DFLC) core and a flow control algorithm that runs under the Xilinx Microblaze soft processor core. The fuzzy controller supports a fuzzy path tracking algorithm introduced by the authors. The FPGA board hosting the SoC was attached to an actual differential-drive Pioneer 3-DX8 robot, which was used in field experiments in order to assess the overall performance of the tracking scheme. Moreover, quantization problems and limitations imposed by the system configuration are also discussed.

Advances in Intelligent Mobility Assistance Robot Integrating Multimodal Sensory Processing

Mobility disabilities are prevalent in our ageing society and impede activities important for the independent living of elderly people and their quality of life. The goal of this work is to support human mobility and thus enforce fitness and vitality by developing intelligent robotic platforms designed to provide user-centred and natural support for ambulating in indoor environments. We envision the design of cognitive mobile robotic systems that can monitor and understand specific forms of human activity, in order to deduce what the human needs are, in terms of mobility. The goal is to provide user and context adaptive active support and ambulation assistance to elderly users, and generally to individuals with specific forms of moderate to mild walking impairment. To achieve such targets, a reliable multimodal action recognition system needs to be developed, that can monitor, analyse and predict the user actions with a high level of accuracy and detail. Different modalities need to be combined into an integrated action recognition system. This paper reports current advances regarding the development and implementation of the first walking assistance robot prototype, which consists of a sensorized and actuated rollator platform. The main thrust of our approach is based on the enhancement of computer vision techniques with modalities that are broadly used in robotics, such as range images and haptic data, as well as on the integration of machine learning and pattern recognition approaches regarding specific verbal and non-verbal gestural commands in the envisaged physical and non-physical human-robot interaction context.

Simplifying mobile robot tracking control through feedback equivalence

In this paper a feedback equivalence map that simplifies the motion control of mobile robots is presented. The map applies to the path tracking and the trajectory tracking tasks for non-holonomic mobile robots. A diffeomorphism that maps the reference path in the original domain, to a straight line in the transformed domain is also introduced. It is shown that this map can be extended to the entire state space and, when applied, the resulting system equations have the same form with the original model. This allows the simplification of motion control since the problem is now reduced to the tracking of straight lines. However, since the models are the same, one can use existing tracking controllers and tailor them to track only straight lines, thus reducing their complexity, or use existing straight line tracking controllers, and apply them to curved reference paths. An analysis of the type of paths that allow for this transformation is also presented along with simulation results.

Intention-based front-following control for an intelligent robotic rollator in indoor environments

This work presents an intention-based assistive controller for allowing a robot to follow a human while moving in the front. This task is particularly challenging in indoor environments, as there are situations that are undecidable, namely in junctions. We propose a novel local kinodynamic planner which concurrently detects discrete routes and continuous motion paths, providing path equivalence classes. Furthermore, we detail an intention recognition algorithm to make the robot take the user-intended turn. Our scheme is experimentally tested in a T-Junction set-up using human subjects, and the results are discussed.

Assistive front-following control of an intelligent robotic rollator based on a modified dynamic window planner

In this paper we present an assistive controller for the front-following task, applied to an intelligent robotic rollator. The control is based on a novel Dynamic Window local planner, which simultaneously treats discrete and continuous planning, by providing path equivalence classes and obstacle-free paths. This enables the detection of undecidability areas, e.g. junctions, as well as the safe locomotion of the robot while following the human. User experiments show that the assistive module, compared to a direct kinematic approach, allows the user to walk more naturally and more similar to his/her normal gait, and reduces the cognitive load.