Robot Experiments Research Articles

An SLAM Algorithm Based on Laser Radar and Vision Fusion with Loop Detection Optimization

SLAM (Simultaneous Localization And Mapping, SLAM) is the key technology for mobile robots to obtain information about their position and surrounding environment, but both laser radar and vision sensors have limitations in solving SLAM problems, for example: a single laser sensor can’t do mapping effectively for hollowed-out obstacles, while a single vision sensor can’t work well in areas without texture. Besides, the existing loop detection technology still has some problems such as large calculation resources and errors. To solve the above problems, an improved SLAM algorithm laser and vision fusion was presented in this paper. In this algorithm, a Gaussian statistical linear interpolation algorithm was used to interpolate the laser point cloud, and then the interpolated laser raster map and visual raster map are fused by the Bayesian method to obtain a denser and more accurate map. Furthermore, the histogram was used to improve the loop detection part to further improve the positioning accuracy. The improved loop detection algorithm was simulated and verified by running the TUM data set. On this basis, a mobile robot experiment system was built to do mapping in the laboratory scene. The experimental results show that the algorithm proposed in this paper can map the hollowed-out area accurately and effectively, it plays a significant role in improving the drawing effect of the robot, and can provide more accurate location information, which has good practicability.

A Resilient and Energy-Aware Task Allocation Framework for Heterogeneous Multirobot Systems

In the context of heterogeneous multirobot teams deployed for executing multiple tasks, this article develops an energy-aware framework for allocating tasks to robots in an online fashion. With a primary focus on long-duration autonomy applications, we opt for a survivability-focused approach. Toward this end, the task prioritization and execution—through which the allocation of tasks to robots is effectively realized—are encoded as constraints within an optimization problem aimed at minimizing the energy consumed by the robots at each point in time. In this context, an allocation is interpreted as a prioritization of a task over all others by each of the robots. Furthermore, we present a novel framework to represent the heterogeneous capabilities of the robots, by distinguishing between the features available on the robots and the capabilities enabled by these features. By embedding these descriptions within the optimization problem, we make the framework resilient to situations, where environmental conditions make certain features unsuitable to support a capability and when component failures on the robots occur. We demonstrate the efficacy and resilience of the proposed approach in a variety of use-case scenarios, consisting of simulations and real robot experiments.

Research on the future of combat robotics on the example of Ukraine

The object of research is the architecture of any combat ground robot in the context of its individual systems and subsystems. The conducted research forms a transparent and clear understanding of the main logical links of a combat robot, individual technologies, and components used in the development and serial production. The paper summarizes the global experience and achievements of combat robotics and provides examples of the example of the development of teams from Ukraine. The mentioned are the main system players in this sector of defense technologies, long-term and productive activity of which resulted in the appearance of the first combat robot units in the armies of the leading countries of the world. The author studied and presented the structural structure of any ground combat robot by the method of deduction and reproduction of functional capabilities. In the context of separate systems or subsystems of a ground combat robot recommendations on the equipment of those or other components, sensors, technologies, or their analogs and other equipment are given. The work summarizes the experience of the head of Robotics Design Bureau LLC (Kyiv, Ukraine), associated with the attention of representatives of foreign companies and government agencies to the Ukrainian developments in this area. The leading idea of the research is the priority development of functions and algorithms of combat robots, associated with the development of vision and autonomous movement systems. Realization of these functions sharply increases the advantages of own combat robots, increases their survivability and combat efficiency, reduces dangers for operators of the equipment. Factors related to the package of impact module subsystems directly affecting the combat effectiveness of a ground robot are presented. Compared to similar known studies on this topic, the research conducted immediately immerses the reader into the practical plane of developing a ground combat robot from the perspective of the engineer-creator, which provides quick basic knowledge and insights and inspires further exploration in this direction.

Human-robot interaction: the impact of robotic aesthetics on anticipated human trust.

BackgroundHuman senses have evolved to recognise sensory cues. Beyond our perception, they play an integral role in our emotional processing, learning, and interpretation. They are what help us to sculpt our everyday experiences and can be triggered by aesthetics to form the foundations of our interactions with each other and our surroundings. In terms of Human-Robot Interaction (HRI), robots have the possibility to interact with both people and environments given their senses. They can offer the attributes of human characteristics, which in turn can make the interchange with technology a more appealing and admissible experience. However, for many reasons, people still do not seem to trust and accept robots. Trust is expressed as a person’s ability to accept the potential risks associated with participating alongside an entity such as a robot. Whilst trust is an important factor in building relationships with robots, the presence of uncertainties can add an additional dimension to the decision to trust a robot. In order to begin to understand how to build trust with robots and reverse the negative ideology, this paper examines the influences of aesthetic design techniques on the human ability to trust robots.MethodThis paper explores the potential that robots have unique opportunities to improve their facilities for empathy, emotion, and social awareness beyond their more cognitive functionalities. Through conducting an online questionnaire distributed globally, we explored participants ability and acceptance in trusting the Canbot U03 robot. Participants were presented with a range of visual questions which manipulated the robot’s facial screen and asked whether or not they would trust the robot. A selection of questions aimed at putting participants in situations where they were required to establish whether or not to trust a robot’s responses based solely on the visual appearance. We accomplished this by manipulating different design elements of the robots facial and chest screens, which influenced the human-robot interaction.ResultsWe found that certain facial aesthetics seem to be more trustworthy than others, such as a cartoon face versus a human face, and that certain visual variables (i.e., blur) afforded uncertainty more than others. Consequentially, this paper reports that participant’s uncertainties of the visualisations greatly influenced their willingness to accept and trust the robot. The results of introducing certain anthropomorphic characteristics emphasised the participants embrace of the uncanny valley theory, where pushing the degree of human likeness introduced a thin line between participants accepting robots and not. By understanding what manipulation of design elements created the aesthetic effect that triggered the affective processes, this paper further enriches our knowledge of how we might design for certain emotions, feelings, and ultimately more socially acceptable and trusting robotic experiences.

Development of a Comprehensive Design Guideline to Evaluate the User Experiences of Meal-Assistance Robots considering Human-Machine Social Interactions

ABSTRACT Meal-assistance robots (MARs) help feed meals to users with disabilities or who need help consuming their meals. Although such MARs have been introduced in various fields, guidelines for evaluating MARs are limited. This study aims to develop comprehensive guidelines to assess the user experience (UX) of MAR designs considering its social interaction characteristics between humans and robots. Participants from three groups (patients, doctors, and caregivers) with different perspectives on MARs were recruited and a focus group interview was conducted to collect their UXs with MARs. The three groups showed different UXs with MARs in user interface design, robot arm motion, and safety and mobility. In addition, based on the literature review, eight UX features (usability, emotion, value, naturalness, assistance, acceptance, personality, and culture) are proposed to evaluate MAR interfaces. The proposed comprehensive design guideline will be particularly useful in evaluating and designing the UX of MARs.

Multivisceral Resection in Robotic Liver Surgery.

Simple SummaryLiver surgery can be performed simultaneously with operations to remove other organs in certain circumstances, such as removal of colorectal cancer in the colon or rectum at the same time as metastatic lesions to the liver. These types of operations have been performed as open or laparoscopic procedures; however, more recently, they can be performed with a robotic approach. In this article, we review the literature and describe robotic liver resections performed with robotic resection of other organs, including colon, rectum, and pancreas. These published reports demonstrate that, in select cases and experienced hands, robotic multivisceral resection can be safely performed with good outcomes.Minimally invasive surgery techniques are expanding in utilization in liver resections and now include robotic approaches. Robotic liver resection has been demonstrated to have several benefits, including surgeon ergonomics, wrist articulation, and 3D visualization. Similarly, for multivisceral liver resections, the use of minimally invasive techniques has evolved and expanded from laparoscopy to robotics. The aim of this article is to review the literature and describe multivisceral resections, including hepatectomy, using a robotic technique. We describe over 50 published cases of simultaneous robotic liver resection with colon or rectal resection. In addition, we describe several pancreatectomies performed with liver resection and one extra-abdominal pulmonary resection with liver resection. In total, these select reported cases at experienced centers demonstrate the safety of robotic multivisceral resection in liver surgery with acceptable morbidity and rare conversion to open surgery. As robotic technology advances and experience with robotic techniques grows, robotic multivisceral resection in liver surgery should continue to be investigated in future studies.

Safety and Feasibility of Robotic Transaxillary Thyroidectomy for Graves' Disease: A Retrospective Cohort Study.

Despite the increase in experience and understanding of robotic thyroidectomy, its application for Graves' disease (GD) remains controversial. This study aimed to assess the safety and feasibility of robotic transaxillary thyroidectomy (RTT) for GD in comparison with the conventional open thyroidectomy (open group: OG) approach. A total of 192 patients who underwent surgical resection for GD were retrospectively reviewed. Among them, 51 patients underwent RTT and the remaining 141 patients were in the conventional OG. All robotic operations were performed successfully without open conversion. Patients who underwent RTT were significantly younger (P < 0.001) and predominantly of the female sex. Operative time was longer for RTT than for the OG (182.5 ± 58.1 vs. 112.0 ± 29.5; P < 0.001). The mean intraoperative blood loss was not statistically different between RTT and the OG (113.3 ± 161.6 vs. 95.3 ± 209.1, P = 0.223). The mean weight of the resected thyroid was reduced in those who underwent RTT compared with open thyroidectomy (P = 0.033). The overall complication rate for RTT and open thyroidectomy was not significantly different (33.3% vs. 22.7%, P = 0.135). In RTT, the most common complication was transient hypocalcemia (21%). Permanent hypocalcemia and recurrent laryngeal nerve injury occurred in only one patient in each group. The weight of the resected thyroid was not related to the incidence of complications in patients receiving RTT. Considering excellent cosmesis, findings of this study support the safety and feasibility of RTT. Nevertheless, it should be performed by expert surgeons with extensive robotic surgery experience.

Impact of caudal fin geometry on the swimming performance of a snake-like robot

Eels and sea snakes are known for long migrations and high endurance cruising and can be great sources of inspiration for underwater robots. This study employs both computational and experimental techniques to explore the impact of caudal fin design on the swimming performance of a snake-like robot. The caudal fin geometry is systematically varied by changing the leading edge and trailing edge angles. Inspired by sea snakes, the robot mimics an anguilliform swimming gait. Robotic experiments and computational fluid dynamics (CFD) simulations are carried out with different caudal fin geometries. The results show that the snake-like robot achieves the best swimming speed and efficiency at an 85°leading edge angle and a 120°convex trailing edge angle. In addition, the numerical simulation results show that the wake structure formed by the snake-like robot consists of two parallel disconnected verse van Karman vortex rings. When the leading edge angle is slightly below 90°the body vortex merges and interacts with the caudal fin’s vortex. This interaction contributes strongly to wake construction and significantly enhances swimming speed and efficiency.

Visual Foresight Trees for Object Retrieval From Clutter With Nonprehensile Rearrangement

This paper considers the problem of retrieving an object from many tightly packed objects using a combination of robotic pushing and grasping actions. Object retrieval in dense clutter is an important skill for robots to operate in households and everyday environments effectively. The proposed solution, Visual Foresight Trees (VFT), intelligently rearranges the clutter surrounding a target object so that it can be grasped easily. Rearrangement with nested nonprehensile actions is challenging as it requires predicting complex object interactions in a combinatorially large configuration space of multiple objects. We first show that a deep neural network can be trained to accurately predict the poses of the packed objects when the robot pushes one of them. The predictive network provides visual foresight and is used in a tree search as a state transition function in the space of scene images. The tree search returns a sequence of consecutive push actions yielding the best arrangement of the clutter for grasping the target object. Experiments in simulation and using a real robot and objects show that the proposed approach outperforms model-free techniques as well as model-based myopic methods both in terms of success rates and the number of executed actions, on several challenging tasks. A video introducing VFT, with robot experiments, is accessible at https://youtu.be/7cL-hmgvyec. The full source code is available at https://github.com/arc-l/vft.

A comprehensive evaluation of sexual and reproductive outcomes following robot-assisted retroperitoneal lymph node dissection for nonseminomatous germ cell tumor.

Sexual disorders following retroperitoneal pelvic lymph node dissection (RPLND) for testis tumor can affect the quality of life of patients. The aim of the current study was to investigate several different andrological outcomes, which may be influenced by robot-assisted (RA) RPLND. From January 2012 to March 2020, 32 patients underwent RA-RPLND for stage I nonseminomatous testis cancer or postchemotherapy (PC) residual mass. Modified unilateral RPLND nerve-sparing template was always used. Major variables of interest were erectile dysfunction (ED), premature ejaculation (PE), dry ejaculation (DE), or orgasm alteration. Finally, fertility as well as the fecundation process (sexual intercourse or medically assisted procreation [MAP]) was investigated. Ten patients (31.3%) presented an andrological disorder of any type after RA-RPLND. Hypospermia was present in 4 (12.5%) patients, DE (International Index of Erectile Function-5 [IIEF-5] &lt;25) in 3 (9.4%) patients, and ED in 3 (9.4%) patients. No PE or orgasmic alterations were described. Similar median age at surgery, body mass index (BMI), number of nodes removed, scholar status, and preoperative risk factor rates were identified between groups. Of all these 10 patients, 6 (60.0%) were treated at the beginning of our robotic experience (2012-2016). Of all 32 patients, 5 (15.6%) attempted to have a child after RA-RPLND. All of these 5 patients have successfully fathered children, but 2 (40.0%) required a MAP. In conclusion, a nonnegligible number of andrological complications occurred after RA-RPLND, mainly represented by ejaculation disorders, but ED occurrence and overall sexual satisfaction deficit should be definitely considered. No negative impact on fertility was described after RA-RPLND.

Research and experiment of service robots with remote telecommunication at a construction site

Research and experiment of service robots with remote telecommunication at a construction site

Performance Evaluation of a Hybrid Thruster for Spherical Underwater Robots

In this paper, a hybrid thruster for spherical underwater robots was developed and its performance was evaluated. The objective of this work was to improve the execution efficiency, multimodality and maneuverability of the autonomous underwater robot (AUV). Firstly, using meshing method, the open-water performance and flow field of individual water-jet and propeller thruster were analyzed. Numerical simulations were calculated and verified using experimental data. Then, the interaction between the hybrid thrusters were discussed, the flow field characteristics and hydrodynamic performance of the hybrid propulsion system were validated through streamline and pressure distribution. Finally, the hybrid propulsion system was designed, the thrust measurement experiments and the basic motion experiments for spherical underwater robot (SUR) using a hybrid thruster were carried out, including water-jet mode, propeller mode and the hybrid mode. The experimental results further verified the performance of the hybrid propulsion system, which meet the requirements of rapidity and flexibility, as well as the feasibility of underwater applications.

A DoS Attacks Detection Aglorithm Based on Snort-BASE for Robotic Arm Control Systems

In response to the frequent safety accidents of industrial robots, this paper designs and implements a safety detection system for robot control. It can perform real-time security detection of robot operations on industrial production lines to improve the security and reliability of robot control systems. This paper designs and implements a robot control system based Snort-BASE for real-time online detection of DoS attacks. The system uses a six-degree-of-freedom robotic arm as an example, uses Snort to record the network communication data of the robot arm control system in real time, and filters the network traffic through self-defined rules, and then uses the BASE analysis platform to achieve security analysis of the network traffic. The solution verifies the effectiveness of online real-time detection of attacks and visualisation of attack records by designing simulated robotic arm and real robotic arm attack experiments respectively, thus achieving the security of network communication of the robot remote control system.

PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization

In this paper, we present a novel end-to-end learning-based LiDAR sensor relocalization framework, termed PointLoc, which infers 6-DoF poses directly using only a single point cloud as input. Compared to visual sensor-based relocalization, LiDAR sensors can provide rich and robust geometric information about a scene. However, point clouds of LiDAR sensors are unordered and unstructured making it difficult to apply traditional deep learning regression models for this task. We address this issue by proposing a novel PointNet-style architecture with self-attention to efficiently estimate 6-DoF poses from 360° LiDAR sensor frames. Extensive experiments on recently released challenging Oxford Radar RobotCar dataset and real-world robot experiments demonstrate that the proposed method can achieve accurate relocalization performance.

Harnessing robot experimentation to optimize the regulatory framing of emerging robot technologies

Abstract From exoskeletons to lightweight robotic suits, wearable robots are changing dynamically and rapidly, challenging the timeliness of laws and regulatory standards that were not prepared for robots that would help wheelchair users walk again. In this context, equipping regulators with technical knowledge on technologies could solve information asymmetries among developers and policymakers and avoid the problem of regulatory disconnection. This article introduces pushing robot development for lawmaking (PROPELLING), an financial support to third parties from the Horizon 2020 EUROBENCH project that explores how robot testing facilities could generate policy-relevant knowledge and support optimized regulations for robot technologies. With ISO 13482:2014 as a case study, PROPELLING investigates how robot testbeds could be used as data generators to improve the regulation for lower-limb exoskeletons. Specifically, the article discusses how robot testbeds could help regulators tackle hazards like fear of falling, instability in collisions, or define the safe scenarios for avoiding any adverse consequences generated by abrupt protective stops. The article’s central point is that testbeds offer a promising setting to bring policymakers closer to research and development to make policies more attuned to societal needs. In this way, these approximations can be harnessed to unravel an optimal regulatory framework for emerging technologies, such as robots and artificial intelligence, based on science and evidence.

Fuzzy logic controlled autonomous quadruped robot

Researchers have taken several steps to build an appropriate 4-point based quadruped robot controller. These efforts can be categorized into analytical and intelligent methods into two main fields. The study of an analytical method is based on the robot’s primarily complex movement equations. On the other hand, an intelligent method requires less knowledge of kinematic and dynamic equations to control the motion and orientation of the quadruped robot autonomously in any environment. In this study, we have chosen the Fuzzy Controller (FC) as an intelligent sensor-actuator control system for the quadruped robot. This robot includes sensors to sense the physical quantities of the environment. And the outputs of the sensors are used as inputs to the FC. According to the sensor inputs and defined rule-based system, the controller gives the actuator control commands to the robot's leg. Further on, the fuzzification and defuzzification modules make decisions that control the robot's motion and allow the robot to navigate automatically. The two-dimensional and three-dimensional models of the quadruped robot have been designed through the SolidWorks software, and the fuzzy controlled simulations of the quadruped robot are presented in the Virtual Robot Experimentation Platform (V-REP) software.

E-puck motion control using multi-objective particle swarm optimization

This article describes the velocity-based motion and orientation control method for a differential-driven two-wheeled E-puck Robot (DDER) using the Multi-Objective Particle Swarm Optimization (MPSO) algorithm in the Virtual Robot Experimentation Platform (V-REP) software environment. The wheel velocities data and Infra-Red (IR) sensors reading make the multi-objective fitness functions for MPSO. We use front, left, and right IR sensors reading and right wheel velocity data to design the first fitness function for MPSO. Similarly, the front, left, and right IR sensors reading, and left wheel velocity data have been taken for making the second fitness function for MPSO. The multi-objective fitness functions of MPSO minimize the motion and orientation of the DDER during navigation. Due to the minimization of motion and orientation, the DDER covers less distance to reach the goal and takes less time. The Two-Dimensional (2D) and Three-Dimensional (3D) navigation results of the DDER among the scattered obstacles have been presented in the V-REP software environment. The comparative analysis with previously developed Invasive Weed Optimization (IWO) algorithm has also been performed to show the effectiveness and efficiency of the proposed MPSO algorithm.

Learning by Breaking: Food Fracture Anticipation for Robotic Food Manipulation

This study aimed to anticipate fractures of fragile food during robotic food manipulation. Anticipating fractures allows a robot to manipulate ingredients without irreversible failure. Food fracture models investigated in food texture fields explain the properties of fragile objects well. However, they may not directly apply to robot manipulation due to the variance in physical properties even within the same ingredient. To this end, we developed a fracture-anticipation system with a tactile sensing module and a simple recurrent neural network. The key idea was to allow the robot to break ingredients during training-sample collection. The timing of fractures was identified via simple signal processing and used for supervision. We performed real robot experiments with three typical fragile foods: tofu, potato chips, and bananas. As the first step toward flexible fragile-object manipulation, we evaluated the proposed method for the fundamental task of object picking. The method successfully grasped the fragile foods without fractures in an online demonstration. In an offline evaluation, the method predicted the fractures with a recall of approximately 80% for all ingredients with 60 breaking trials. We believe that our method can be used to avoid breakage in other types of food manipulation, e.g., holding, pressing, and rolling.

Selective Inflow Pringle Maneuver during Robotic Partial Right Hepatectomy

Introduction: Pringle maneuver has been traditionally used to minimize hemorrhage during hepatectomy. Although effective, it has been associated with ischemic liver injury particularly in patients with underlying liver disease or when a long parenchymal transection is anticipated. Selective inflow Pringle (SIP) technique has been previously utilized to minimize ischemia time while achieving minimal blood loss, however the minimally invasive robotic experience with this approach is limited.

Real-time cooperative kinematic control for multiple robots in distributed scenarios with dynamic neural networks

This work investigates the real-time cooperative kinematic control for multiple robots in distributed scenarios. The information interaction among robots is described as a directed topology in which each robotic manipulator is connected to specified nodes. Besides, a performance index of minimum joint velocity norm is introduced to regulate the robots’ motion. Combining with the performance index and integrating the related constraints, a control scheme is developed to guide the behavior of robots with an error feedback term leveraged to improve the real-time execution accuracy of tasks. Moreover, considering that the involved parameters are time-dependent, a dynamic neural-network-assisted solver is constructed to solve the control scheme online. In the end, simulations and illustrative experiments on the virtual robot experiment platform (V-REP) are conducted by a set of UR5 robots to execute tasks in a switchable directed topology, where the corresponding results demonstrate the effectiveness of the proposed scheme.