Experimental Robotic Platform Research Articles

Virtual-force-guided intraoperative ultrasound scanning with online lesion location prediction: A phantom study.

In ultrasound-guided minimally invasive surgery (MIS) of tumours, it is crucial to discover the optimal scanning plane (OSP) and organise the MIS scalpel work trajectory in this plane. The OSP can be altered and is challenging to track when the scalpel interacts with deformed tissues. Therefore, tracking the OSP becomes critical in MIS. In master-slave control, virtual force (VF) is used to assist the operator in completing the task. However, most literature assumes that the environment is sufficiently stable. No specific method focuses on tracking the OSP of the lesion within largely deformed tissues. This paper used the improved artificial potential field method to establish the VF that could guide the operator to track the OSP. When tissue deformation occurred, an artificial neural network (ANN) was used to predict the target position, guiding the operator to find the new OSP. An experimental robot platform was built to verify the proposed algorithm's effects. Experiments to track the OSP were performed on a phantom. The results showed that the presented method could reduce the trajectory redundancy of ultrasonic scanning, shorten the time of OSP discovery and tracking, and decrease the deviation between the ultrasonic scanning position and the OSP. This method has significance for the accurate localization and successful removal of tumours. Future work will focus on improving the adaptability of the proposed ANN prediction model in different phantoms.

Multi-Arm Global Cooperative Coal Gangue Sorting Method Based on Improved Hungarian Algorithm.

The existing multi-manipulator sorting method for gangue that utilizes a multi-task allocation strategy is not satisfactory. The single manipulator working space is fixed, lowering the cooperation degree between the manipulators and leading to a low sorting rate. Therefore, this paper proposes a multi-manipulator cooperative sorting method that can work globally. First, a benefit function based on the sorting time and quality of the gangue is constructed by combining the gangue flow information and the manipulator state. The time parameter is obtained via the manipulator’s dynamic target tracking trajectory planning algorithm based on PID control. Secondly, the benefits matrix is standardized and updated many times to improve the Hungarian algorithm to achieve task allocation, and the initial solution with priority is obtained. Finally, the solutions are analyzed and processed cooperatively in order of priority. The conflicts between multiple robotic arms are eliminated through task cooperation and trajectory cooperation until the sorting task that the robot arm can execute is obtained from the allocation results. Experiments involving different sorting methods were completed on a multi-arm coal and gangue sorting experimental robot platform. The experimental results show that the sorting efficiency of the proposed method is about 10% and 20% higher than that of the fixed space dynamic and designated space fixed points methods, respectively, under different belt speeds. This method can guarantee system benefits, effectively implements cooperative control of multi-manipulator operations in the whole area, and improves the efficiency of coal gangue sorting.

Intelligent Sampling of Anterior Human Nasal Swabs using a Collaborative Robotic Arm

Advanced robotics does not always have to be associated with Industry 4.0, but can also be applied, for example, in the Smart Hospital concept. Developments in this field have been driven by the coronavirus disease (COVID-19), and any improvement in the work of medical staff is welcome. In this paper, an experimental robotic platform was designed and implemented whose main function is the swabbing samples from the nasal vestibule. The robotic platform represents a complete integration of software and hardware, where the operator has access to a web-based application and can control a number of functions. The increased safety and collaborative approach cannot be overlooked. The result of this work is a functional prototype of the robotic platform that can be further extended, for example, by using alternative technologies, extending patient safety, or clinical tests and studies. Code is available at https://github.com/Steigner/Robo_Medicinae_I

Faster Confined Space Manufacturing Teleoperation Through Dynamic Autonomy With Task Dynamics Imitation Learning

Confined space manufacturing tasks, such as cleaning pilot holes prior to installing fasteners during aircraft wing assembly, currently require human experts to be inside ergonomically-challenging environments. Small rapidly deployable robots can substantially improve manufacturing safety and productivity. However, relatively rapid full automation remains elusive due to high-level of uncertainty in the environment, lack of cost-effective programming for low volume production, and difficulty of deploying adequate number of sensors in the confined space. Moreover, currently, teleoperation (remote human control of a robot via a force-reflection device) with typical levels of training and limited transparency of hardware is too slow for manufacturing applications, requiring experts to spend more time for each task to achieve the same cleaning quality. In this context, the main contribution of this article is to reduce cycle times for remote manufacturing by learning statistical dynamic autonomy from higher quality expert demonstrations in an ideal offline scenario. During the task, to keep cycle times low, the dynamic autonomy imitates the faster expert demonstrations when certain, and employs the slower human teleoperation when uncertain. A user study (n = 8) with an experimental robot platform shows that for the same cleaning quality, the dynamic autonomy reduces process completion time by 54.0% and human operator energy expenditure by 80.5% as compared with teleoperation without dynamic autonomy.

Tuna robotics: A high-frequency experimental platform exploring the performance space of swimming fishes.

Tuna and related scombrid fishes are high-performance swimmers that often operate at high frequencies, especially during behaviors such as escaping from predators or catching prey. This contrasts with most fish-like robotic systems that typically operate at low frequencies (< 2 hertz). To explore the high-frequency fish swimming performance space, we designed and tested a new platform based on yellowfin tuna (Thunnus albacares) and Atlantic mackerel (Scomber scombrus). Body kinematics, speed, and power were measured at increasing tail beat frequencies to quantify swimming performance and to study flow fields generated by the tail. Experimental analyses of freely swimming tuna and mackerel allow comparison with the tuna-like robotic system. The Tunabot (255 millimeters long) can achieve a maximum tail beat frequency of 15 hertz, which corresponds to a swimming speed of 4.0 body lengths per second. Comparison of midline kinematics between scombrid fish and the Tunabot shows good agreement over a wide range of frequencies, with the biggest discrepancy occurring at the caudal fin, primarily due to the rigid propulsor used in the robotic model. As frequency increases, cost of transport (COT) follows a fish-like U-shaped response with a minimum at ~1.6 body lengths per second. The Tunabot has a range of ~9.1 kilometers if it swims at 0.4 meter per second or ~4.2 kilometers at 1.0 meter per second, assuming a 10-watt-hour battery pack. These results highlight the capabilities of high-frequency biological swimming and lay the foundation to explore a fish-like performance space for bio-inspired underwater vehicles.

Android Corporeality, Transhuman Performance and the Japanese ‘Mind’

This essay examines Alter, an android that was developed collaboratively by Japanese roboticist Hiroshi Ishiguro and A-Life (artificial life) scientist Takashi Ikegami. Alter is an experimental robot platform conceived as a ‘machine human’. Alter was created at the juncture of Ishiguro’s interest in android appearance and Ikegami’s search for what he sees as internal principles underlying life. While Ishiguro’s anthropomorphic machines are intended as models for future humanoid robots in workplaces and domestic contexts, they are also intended as experimental tools for his investigations on human identity, the ‘soul’, and sociality, and related philosophical questions, such as ‘What is the human?’ In contrast, Ikegami works with a different question: ‘What is natural life?’ Ikegami’s question emerges from his research interest in and development of artificial life systems, which combine computer simulation, chemical experiments, and robotics. Alter, presented as an interactive performance installation at a science museum in Japan in 2016, was intended as a model with which to study human embodiment and sentience. In this essay, I examine how Alter’s 2016 performance was designed dramaturgically to induce a sense of agency hovering between the organic and the inorganic, the natural and mechanical, the random and controlled, and between the autonomous and programmed. I discuss how Alter rehearsed human-machine inter-corporeality, and how its dramaturgical staging contributed to its agency.

Cooperative Wireless-Based Obstacle/Object Mapping and See-Through Capabilities in Robotic Networks

In this paper, we develop a theoretical and experimental framework for the mapping of obstacles (including occluded ones), in a robotic cooperative network, based on a small number of wireless channel measurements. This would allow the robots to map an area before entering it. We consider three approaches based on coordinated space, random space, and frequency sampling, and show how the robots can exploit the sparse representation of the map in space, wavelet or spatial variations, in order to build it with minimal sensing. We then show the underlying tradeoffs of all the possible sampling, sparsity and reconstruction techniques. Our simulation and experimental results show the feasibility and performance of the proposed framework. More specifically, using our experimental robotic platform, we show preliminary results in successfully mapping a number of real obstacles and having see-through capabilities with real structures, despite the practical challenges presented by multipath fading.

Exoskeleton-Based Robotic Platform Applied in Biomechanical Modelling of the Human Upper Limb

One of the approaches to study the human motor system, and specifically the motor strategies implied during postural tasks of the upper limbs, is to manipulate the mechanical conditions of each joint of the upper limbs independently. At the same time, it is essential to pick up biomechanical signals and bio-potentials generated while the human motor system adapts to the new condition. The aim of this paper is two-fold: first, to describe the design, development and validation of an experimental platform designed to modify or perturb the mechanics of human movement, and simultaneously acquire, process, display and quantify bioelectric and biomechanical signals; second, to characterise the dynamics of the elbow joint during postural control. A main goal of the study was to determine the feasibility of estimating human elbow joint dynamics using EMG-data during maintained posture. In particular, the experimental robotic platform provides data to correlate electromyographic (EMG) activity, kinetics and kinematics information from the upper limb motion. The platform aims consists of an upper limb powered exoskeleton, an EMG acquisition module, a control unit and a software system. Important concerns of the platform such as dependability and safety were addressed in the development. The platform was evaluated with 4 subjects to identify, using system identification methods, the human joint dynamics, i.e. visco-elasticity. Results obtained in simulations and experimental phase are introduced.

EMOTION EXPRESSION AND ENVIRONMENT THROUGH AFFECTIVE INTERACTION

This paper focuses on emotion expressions and environments through affective interaction between a human and a robot. To this end, we develop an emotion expression system includes an emotion engine, an experimental platform and a simulation tool. KOBIE is an experimental robot platform which provides emotional stability and continuous interest to a user through affective interaction. In addition, the simulation tool provides a visualization interface for the emotion engine and expresses emotion through an avatar. The proposed system can be used in the development of cyber characters that use emotions or in the development of an apparatus with emotion in a ubiquitous environment.

Exoskeleton‐Based Robotic Platform Applied in Biomechanical Modelling of the Human Upper Limb

One of the approaches to study the human motor system, and specifically the motor strategies implied during postural tasks of the upper limbs, is to manipulate the mechanical conditions of each joint of the upper limbs independently. At the same time, it is essential to pick up biomechanical signals and bio‐potentials generated while the human motor system adapts to the new condition. The aim of this paper is two‐fold: first, to describe the design, development and validation of an experimental platform designed to modify or perturb the mechanics of human movement, and simultaneously acquire, process, display and quantify bioelectric and biomechanical signals; second, to characterise the dynamics of the elbow joint during postural control. A main goal of the study was to determine the feasibility of estimating human elbow joint dynamics using EMG‐data during maintained posture. In particular, the experimental robotic platform provides data to correlate electromyographic (EMG) activity, kinetics and kinematics information from the upper limb motion. The platform aims consists of an upper limb powered exoskeleton, an EMG acquisition module, a control unit and a software system. Important concerns of the platform such as dependability and safety were addressed in the development. The platform was evaluated with 4 subjects to identify, using system identification methods, the human joint dynamics, i.e. visco‐elasticity. Results obtained in simulations and experimental phase are introduced.