Safe Robot Research Articles

A human-centered safe robot reinforcement learning framework with interactive behaviors.

Deployment of Reinforcement Learning (RL) algorithms for robotics applications in the real world requires ensuring the safety of the robot and its environment. Safe Robot RL (SRRL) is a crucial step toward achieving human-robot coexistence. In this paper, we envision a human-centered SRRL framework consisting of three stages: safe exploration, safety value alignment, and safe collaboration. We examine the research gaps in these areas and propose to leverage interactive behaviors for SRRL. Interactive behaviors enable bi-directional information transfer between humans and robots, such as conversational robot ChatGPT. We argue that interactive behaviors need further attention from the SRRL community. We discuss four open challenges related to the robustness, efficiency, transparency, and adaptability of SRRL with interactive behaviors.

Encoding the Enforcement of Safety Standards into Smart Robots to Harness Their Computing Sophistication and Collaborative Potential: A Legal Risk Assessment for European Union Policymakers

Abstract Until robots and humans mostly worked in fast-paced and yet separate environments, occupational health and safety (OHS) rules could address workers’ safety largely independently from robotic conduct. This is no longer the case: collaborative robots (cobots) working alongside humans warrant the design of policies ensuring the safety of both humans and robots at once, within shared spaces and upon delivery of cooperative workflows. Within the European Union (EU), the applicable regulatory framework stands at the intersection between international industry standards and legislation at the EU as well as Member State level. Not only do current standards and laws fail to satisfactorily attend to the physical and mental health challenges prompted by human–robot interaction (HRI), but they exhibit important gaps in relation to smart cobots (“SmaCobs”) more specifically. In fact, SmaCobs combine the black-box unforeseeability afforded by machine learning with more general HRI-associated risks, towards increasingly complex, mobile and interconnected operational interfaces and production chains. Against this backdrop, based on productivity and health motivations, we urge the encoding of the enforcement of OHS policies directly into SmaCobs. First, SmaCobs could harness the sophistication of quantum computing to adapt a tangled normative architecture in a responsive manner to the contingent needs of each situation. Second, entrusting them with OHS enforcement vis-à-vis both themselves and humans may paradoxically prove safer as well as more cost-effective than for humans to do so. This scenario raises profound legal, ethical and somewhat philosophical concerns around SmaCobs’ legal personality, the apportionment of liability and algorithmic explainability. The first systematic proposal to tackle such questions is henceforth formulated. For the EU, we propose that this is achieved through a new binding OHS Regulation aimed at the SmaCobs age.

A Path Planning Algorithm of Inspection Robots for Solar Power Plants Based on Improved RRT*

In order to improve the safety and efficiency of inspection robots for solar power plants, the Rapidly Exploring Random Tree Star (RRT*) algorithm is studied and an improved method based on an adaptive target bias and heuristic circular sampling is proposed. Firstly, in response to the problem of slow search speed caused by random samplings in the traditional RRT* algorithm, an adaptive target bias function is applied to adjust the generation of sampling points in real-time, which continuously expands the random tree towards the target point. Secondly, to solve the problem that the RRT* algorithm has a low search efficiency and stability in narrow and long channels of solar power plants, the strategy of heuristic circular sampling combined with directional deviation is designed to resample nodes located on obstacles to generate more valid nodes. Then, considering the turning range of the inspection robot, our method will prune nodes on the paths that fail to meet constraint of the minimum turning radius. Finally, the B-spline curve is used to fit and smooth the path. A simulation experiment based on the environment of solar power plant is conducted and the result demonstrates that, compared with the RRT*, the improved RRT* algorithm reduces the search time, iterations, and path cost by 62.06%, 45.17%, and 1.6%, respectively, which provides a theoretical basis for improving the operational efficiency of inspection robots for solar power plants.

Research on methods of improving safety for collaborative robot

Recently, robotics research has gradually shifted its focus to studying the characteristics of human-robot cooperation in industrial production applications in order to combine the precision and power of robots with human perception and flexibility. For this purpose, a new generation of robots, known as collaborative robots, or cobots, was born. The characteristic of cobots is to work collaboratively with humans without physical barriers, so human safety is always a top priority. In the scope of this research, the authors provide a synthesis of methods to improve safety for collaborative robots. Then, the authors suggest some future development directions in order to not only ensure safety but also improve the working efficiency of cobots

Data-Based Shape Self-Sensing of a Cable-Driven Notched Continuum Mechanism Using Multidimensional Intrinsic Force Information for Surgical Robot

Abstract The accurate shape-sensing capability of the continuum mechanism is fundamental to improve and guarantee the motion control accuracy and safety of continuum surgical robots. This paper presents a data-based shape self-sensing method for a cable-driven notched continuum mechanism using its multidimensional intrinsic force information, which mainly includes the multidimensional forces/torques and driving cable tensions. The nonlinear hysteresis compensation and the shape estimation of the notched continuum mechanism play significant roles in its motion control. Calibration compensation of the notched continuum mechanism is performed based on kinematic modeling to improve the accuracy of its preliminary motion control. The hysteresis characteristics of the continuum mechanism are analyzed, modeled, and compensated through considering the abundant dynamic motion experiments, such that a feedforward hysteresis compensation controller is designed to improve the tracking control performance of the continuum mechanism. Based on the kinematic calibration and hysteresis compensation, combined with the motor displacement, driving cable tensions, and six-dimensional forces/torques information of the continuum mechanism, a data-based shape self-sensing method based on particle swarm optimization back propagation neural network (PSO-BPNN) is proposed in this study. Experimental results show that this method can effectively estimate the loaded and unloaded shape of the notched continuum mechanism, which provides a new approach for the shape reconstruction of cable-driven notched continuum surgical robots.

A safe reinforcement learning approach for autonomous navigation of mobile robots in dynamic environments

AbstractWhen deploying mobile robots in real‐world scenarios, such as airports, train stations, hospitals, and schools, collisions with pedestrians are intolerable and catastrophic. Motion safety becomes one of the most fundamental requirements for mobile robots. However, until now, efficient and safe robot navigation in such dynamic environments is still an open problem. The critical reason is that the inconsistency between navigation efficiency and motion safety is greatly intensified by the high dynamics and uncertainties of pedestrians. To face the challenge, this paper proposes a safe deep reinforcement learning algorithm named Conflict‐Averse Safe Reinforcement Learning (CASRL) for autonomous robot navigation in dynamic environments. Specifically, it first separates the collision avoidance sub‐task from the overall navigation task and maintains a safety critic to evaluate the safety/risk of actions. Later, it constructs two task‐specific but model‐agnostic policy gradients for goal‐reaching and collision avoidance sub‐tasks to eliminate their mutual interference. Then, it further performs a conflict‐averse gradient manipulation to address the inconsistency between two sub‐tasks. Finally, extensive experiments are performed to evaluate the superiority of CASRL. Simulation results show an average 8.2% performance improvement over the vanilla baseline in eight groups of dynamic environments, which is further extended to 13.4% in the most challenging group. Besides, forty real‐world experiments fully illustrated that the CASRL could be successfully deployed on a real robot.

Robust safety zones for manipulators with uncertain dynamics in collaborative robotics

ABSTRACT In this paper, an approach for computing online safety zones for collaborative robotics in a robust way, despite uncertain robot dynamics, is proposed. The strategy implements the speed and separation monitoring paradigm, and considers human and robot enclosed in bounding volumes. The human-robot collaboration is monitored by a supervisory controller that guides the robot to stop along a path-consistent trajectory in case of collision danger between human and robot. The size of the robot safety zone is minimized online according to the stop time of the manipulator, and the uncertain robot dynamics is considered using interval arithmetic to ensure compliance with the joint torques limits even in case of imperfect knowledge of the dynamic model parameters. The results verify the effectiveness of the proposed approach, and evaluate the influence of dynamics variations on human-robot collaboration.

CUSTOMIZING TEXTILE AND TACTILE SKINS FOR INTERACTIVE INDUSTRIAL ROBOTS

Abstract Textiles are a promising material for building tactile skins because they are lightweight, flexible, and can conform to complex surfaces. They enhance robot-human interaction by localizing contact points and measuring contact forces. This paper presents a solution for rapidly fabricating, calibrating, and deploying these skins on industrial robot arms. The novel automated skin calibration procedure maps skin locations to robot geometry and calibrates contact force. Through experiments on a FANUC LR Mate 200id/7L industrial robot, we demonstrate that tactile skins made from textiles can be effectively used for human-robot interaction in industrial environments. We demonstrated the following: 1) modifying trajectories using human contact signals and 2) improving force interactions with humans using tactile skins This work presents a comprehensive solution for rapidly fabricating, calibrating, and deploying textile and tactile skins for interactive industrial robots. Our contributions are as follows: 1) we introduce a method for determining skin parameters based on robot geometry; 2) we propose an automated skin calibration process that calibrates both the position and force reading from the skin to the robot; and 3) we demonstrate how the skins can be integrated into robot control and learning to improve the safety and interactivity of industrial robots through experiments on a FANUC LR Mate 200id/7L industrial robot arm.

Comparison of the safety, effectiveness, and usability of swab robot vs. manual nasopharyngeal specimen collection

BackgroundHealthcare workers face a risk of infection during aerosol-generating procedures, such as nasal swabbing. Robot-assisted nasopharyngeal sampling aims to minimize this risk and reduce stress for healthcare providers. However, its effectiveness and safety require validation. MethodsWe conducted a controlled trial with 80 subjects at two teaching hospitals and compared robot-collected vs manually-collected nasopharyngeal swabs. The primary outcomes included specimen quality and success rate of nasopharyngeal swab collection. We also recorded the pain index, duration of the collection, and psychological stress using a post-collection questionnaire. ResultsDuring the study period, from September 23 to October 27, 2020, 40 subjects were enrolled in both the robotic and manual groups. The cycle threshold (Ct) value for nasopharyngeal specimens was statistically higher in the robotic group compared to the manual group (30.9 vs 28.0, p < 0.01). Both groups had Ct values under 35, indicating good quality specimens. In the robotic group, 3 out of 40 subjects required a second attempt at specimen collection, resulting in a success rate of 92.5 %. Further, although the pain levels were lower in the robotic group, the difference was not statistically significant (2.8 vs 3.6, p = 0.07). The manual group had a shorter sampling time, which was 29 s (201 vs 29, p < 0.05). However, when factoring in the time needed to put on personal protective equipment, the average time for the manual group increased to 251 s (201 vs 251, p < 0.05). Participants' questionnaire results show comparable psychological stress in both groups. Medical staff expressed that using a robot would reduce their psychological stress. ConclusionsWe propose a safe and effective robotic technology for collecting nasopharyngeal specimens without face-to-face contact, which may reduce the stress of physicians and nurses. This technology can also be optimized for efficiency, making it useful in situations where droplet-transmitted infectious diseases are a concern.

Comparison of effectiveness and safety of Da Vinci robot's "3 + 1" and "4 + 1" modes of treatment for colorectal cancer.

To compare the effectiveness of the Da Vinci Surgical Robot System (DSRS) "3 + 1" and "4 + 1" models for colorectal cancer (CRC). A total of 107 patients with CRC admitted to our hospital from February 2021 to May 2022 were selected for the retrospective analysis. Of these, 57 patients underwent the DSRS "4 + 1" model (control group), while the rest 50 underwent the DSRS "3 + 1" model (research group). The operation time, intraoperative bleeding, number of lymph nodes detected, time of first postoperative urinary catheter removal, time of first feeding, time of first venting and hospitalization were compared between the two groups. The changes of white blood cell (WBC) and C-reactive protein (CRP) levels before and after surgery were detected, and patients' adverse effects and treatment costs between surgery and hospital discharge were counted. The Self-Rating Anxiety Scale (SAS) and the Self-Rating Depression Scale (SDS) were used to assess the psychological state of the patients. There was no difference in operative time, intraoperative bleeding, and number of lymph nodes detected between both groups (P > 0.05), while time to first postoperative urinary catheter removal, time to first feeding, time to first venting, length of stay (LOS), postoperative inflammatory factor levels, incidence of adverse events, and treatment costs were all lower in the research group than in the control group (P < 0.05). SAS and SDS scores decreased after treatment in both groups, but the decrease was more obvious in the research group (P < 0.05). Both DSRS "4 + 1" and "3 + 1" modes have better treatment effects for CRC. However, the "3 + 1" mode has higher safety and lower treatment cost, which can significantly improve the postoperative recovery process of patients and is more worthy to be promoted in clinical practice.

Criminal risks of medical robots turnover

Objective: to identify criminal risks inherent in a medical robot, taking into account its hardware-technological (technological and digital) features, and to construct, based on this analysis, the author’s classification of criminal risks and models of criminal-legal protection of public relations arising in the medical robots’ turnover.Methods: the article uses general scientific (analysis, synthesis, induction, deduction, classification) and specific scientific methods of cognition, and the logical-legal method.Results: The security vulnerability of medical robots causes serious concern in manufacturers, programmers and those interacting with the robots in the healthcare industry. In medical institutions, robots interact closely with children, the elderly and the disabled, and it may not be clear to the patient whether the robot is working properly or being attacked. Any harm caused by a surgical robot as a result of unauthorized access (or other illegal actions) can undermine the public’s faith in medicine and in the healthcare system as a whole. Threats to the safety of medical robots can have further negative consequences for themselves, as such facts of unlawful influence can lead to robots breaking down or harming other nearby equipment that is the property of the healthcare institution, and worse – the life and health of patients or medical workers. In this regard, the paper identifies criminal risks and threats inherent in medical robots, and formulates measures to improve criminal legislation aimed at countering crimes arising against the legal turnover of medical robots (Article 2352 of the Criminal Code of the Russian Federation).Scientific novelty: at the moment there are few Russian studies devoted to the legal regulation and protection of medical robots. Basically, such researches are done by medical scientists. However, in the Russian Federation, there are practically no special theoretical-legal studies, including those devoted to the study of criminal law issues of the protection of these legal relations, which confirms the relevance and significance of our research.Practical significance: the provisions and conclusions of the article can be used to further improve criminal legislation, and also lay the foundation for further research in criminal law science.

Research on dynamic parameter identification and collision detection method for cooperative robots

PurposeThe safety performance of cooperative robots is particularly important. This paper aims to study collision detection and response of cooperative robots, which meet the lightweight requirements of cooperative robots and help to ensure the safety of humans and robots.Design/methodology/approachThis paper proposes a collision detection, recognition and response method based on dynamic models. First, this paper identifies the dynamic model of the robot. Second, an external torque observer is established based on the model, and a dynamic threshold collision detection method is designed to reduce the interference of model uncertainty on collision detection. Finally, a collision position and direction estimation method is designed, and a robot collision response strategy is proposed to reduce the harm caused by collisions to humans.FindingsComparative experiments are conducted on static threshold and dynamic threshold collision detection, and the results showed that the static threshold only detected one collision while the dynamic threshold could detect all collisions. Conducting collision position and direction estimation and collision response experiments, and the results show that this method can determine the location and direction of collision occurrence, and enable the robot to achieve collision separation.Originality/valueThis paper designs a dynamic threshold collision detection method that does not require external sensors. Compared with static threshold collision detection methods, this method can significantly improve the sensitivity of collision detection. This paper also proposes a collision position direction estimation method and collision separation response strategy, which can enable robots to achieve post collision separation and improve the safety of cooperative robots.

Combined denoising method of acceleration signal during mobile robot collision

Collision safety of mobile robot is one of the important indexes of robot safety evaluation. The acceleration signal of the robot can completely feed-back the state of the collision process, but it is also vulnerable to noise interference such as vibration and impact, which is difficult to be used for direct analysis. In order to solve the problem of mixing acceleration signal with impact noise and periodic vibration noise during robot collision, a combined filtering noise reduction method based on empirical mode decomposition (EMD), improved wavelet threshold method and dynamic sliding window is proposed. And a wavelet adaptive threshold function is constructed. The wavelet coefficients are automatically adjusted using the information of decomposition degree and noise level, and a dynamic adjustment strategy of sliding window length is designed. The acceleration information of robot can be effectively extracted in the process of strong noise collision. The experimental results show that this method has better noise reduction effect than other methods.

A Study on Standard for Safety Requirements for Care Robots.

Recently, care robots are being developed that incorporate robotics into assistive products that focus on daily care for the physically disabled or elderly with reduced physical function. However, although care robots can reduce the physical burden of human intervention, they can also be dangerous depending on their situational awareness. This study describes a standardization that defines safety requirements for care robots and includes verification methods to test their safety requirements. As an example of the application of this standard, a standard for the safety and performance method of a feeding robot is shown. This standardization study is expected to contribute to the spread of care robots in the future.

A randomized clinical trial to evaluate transoral head and neck surgery using a single-port flexible robotic system

This randomized IDEAL stage 2 clinical trials examined the safety and efficacy of a novel single-port flexible robot for transoral robotic surgery in patients with benign and malignant head and neck tumors. Rates of conversion and perioperative problems within a month of surgery were the main objectives. The Fisher's exact test and the Mann-Whitney U test were used in the statistical analysis, which used a p-value of 0.05 or less to determine significance. With the use of the da Vinci SP technology, 25 participants got TORS that allowed them to swiftly enter their nasopharynx, oropharynx, and hypopharynx. Notably, there were no serious complications or unfavorable robot-related occurrences throughout the 30-day follow-up period or any modifications to the robotic surgical equipment. The novel single-port flexible automated device demonstrates both security and practicality for carrying out transoral endoscopic procedures for head and neck conditions; based on this possible IDEAL stage 2 clinical trials, allowing accessibility to several anatomical regions, such as the larynx, oropharynx, nasopharynx, and hypopharynx.

A GSM-Based Intelligent Monitoring System for Improving Robotics Laboratory Safety

Incorporating industrial robots into current robotics curricula has become a key component for engineering and technology programs. Recently, Toyota Motor Engineering &amp;amp; Manufacturing North America donated a Kawasaki ZB150S industrial robot to the Engineering Technology Programs at Northern Kentucky University. The entire Kawasaki industrial robot system was installed in a safeguard cage; however, the safeguard cage was not always able to prevent unauthorized students from coming into the working area of the robot. The lab manager/staff expressed an urgent need for a smart tool that could monitor occurrences of unauthorized operating conditions to help them improve laboratory safety. Thus, a Global System for Mobile (GSM)-based intelligent monitoring system has been designed and developed to provide a safe robotics lab operating environment for students. This intelligent monitoring system was divided into two subsystems: one was the Embedded Laboratory Environmental Monitoring and Robot Power Control (ELEMRPC) subsystem; the other was the GSM communication subsystem. The ELEMRPC subsystem received the presence-sensing signals from the light curtains at the cage entrance and disarmed the power supply of the robot when unauthorized students were detected. Additionally, the lab environmental parameters were monitored. The GSM subsystem wirelessly transmitted text messages (e.g., lab safety information) to designated cellular phones. These text notifications can alert lab manager/staff immediately to prevent potential accidents within the footprint of the robot safety cage. This paper discusses in greater detail the design, development, and hardware implementation of the robotics laboratory safety monitoring system.

Safety by simulation: theorizing the future of robot regulation

Mobility robots may soon be among us, triggering a need for safety regulation. Robot safety regulation, however, remains underexplored, with only a few articles analyzing what regulatory approaches could be feasible. This article offers an account of the available regulatory strategies and attempts to theorize the effects of simulation-based safety regulation. The article first discusses the distinctive features of mobility robots as regulatory targets and argues that emergent behavior constitutes the key regulatory concern in designing robot safety regulation regimes. In contrast to many accounts, the article posits that emergent behavior dynamics do not arise from robot autonomy, learning capability, or code unexplainability. Instead, they emerge from the complexity of robot technological constitutions coupled with near-infinite environmental variability and non-linear performance dynamics of the machine learning components. Second, the article reviews rules-based and performance-based regulation and argues that both will fail adequately constrain emergent robot behaviors. The article claims that controlling mobility robots requires a simulation-based regulatory approach. Simulation-based regulation is a novelty with significant theoretical and practical implications. The article argues that the approach signifies a radical break in regulatory forms of knowledge and temporalities. Simulations enact virtual futures to create a new regulatory knowledge type. Practically, the novel safety knowledge type may destabilize the existing conceptual space of safety politics and liability allocation patterns.

A Taxonomy of Factors Influencing Perceived Safety in Human–Robot Interaction

Safety is a fundamental prerequisite that must be addressed before any interaction of robots with humans. Safety has been generally understood and studied as the physical safety of robots in human–robot interaction, whereas how humans perceive these robots has received less attention. Physical safety is a necessary condition for safe human–robot interaction. However, it is not a sufficient condition. A robot that is safe by hardware and software design can still be perceived as unsafe. This article focuses on perceived safety in human–robot interaction. We identified six factors that are closely related to perceived safety based on the literature and the insights obtained from our user studies. The identified factors are the context of robot use, comfort, experience and familiarity with robots, trust, the sense of control over the interaction, and transparent and predictable robot actions. We then made a literature review to identify the robot-related factors that influence perceived safety. Based the literature, we propose a taxonomy which includes human-related and robot-related factors. These factors can help researchers to quantify perceived safety of humans during their interactions with robots. The quantification of perceived safety can yield computational models that would allow mitigating psychological harm.

Rule-Based Safe Probabilistic Movement Primitive Control via Control Barrier Functions

In this paper, we develop a novel and safe control design approach that takes demonstrations provided by a human teacher to enable a robot to accomplish complex manipulation scenarios in dynamic environments. First, an overall task is divided into multiple simpler subtasks that are more appropriate for learning and control objectives. Then, by collecting human demonstrations, the subtasks that require robot movement are modeled by probabilistic movement primitives (ProMPs). We also study two strategies for modifying the ProMPs to avoid collisions with environmental obstacles. Finally, we introduce a rule-base control technique by utilizing a finite-state machine along with a unique means of control design for ProMPs. For the ProMP controller, we propose control barrier and Lyapunov functions to guide the system along a trajectory within the distribution defined by a ProMP while guaranteeing that the system state never leaves more than a desired distance from the distribution mean. This allows for better performance on nonlinear systems and offers solid stability and known bounds on the system state. A series of simulations and experimental studies demonstrate the efficacy of our approach and show that it can run in real time. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is motivated by the need to create a teach-by-demonstration framework that captures the strengths of movement primitives and verifiable, safe control. We provide a framework that learns safe control laws from a probability distribution of robot trajectories through the use of advanced nonlinear control that incorporates safety constraints. Typically, such distributions are stochastic, making it difficult to offer any guarantees on safe operation. Our approach ensures that the distribution of allowed robot trajectories is within an envelope of safety and allows for robust operation of a robot. Furthermore, using our framework various probability distributions can be combined to represent complex scenarios in the environment. It will benefit practitioners by making it substantially easier to test and deploy accurate, efficient, and safe robots in complex real-world scenarios. The approach is currently limited to scenarios involving static obstacles, with dynamic obstacle avoidance an avenue of future effort.

Research on the Reliability of a Two-Robot Security System with Early Warning Function

In this paper, the mathematical model of a kind of two-robot security system with an early warning function is studied. By using strongly continuous operator semigroup theory and Volterra integral equation theory, the properties of the semigroup of the system operator, the existence and uniqueness of nonnegative solution, and the well-posedness of solution are discussed, respectively. Under the assumption that the failure rate and repair rate of the system are constants, the equations of the robot system are transformed into an ordinary differential equation group, and then the instantaneous reliability and stable-state reliability of the system are obtained. The reliability and zero-state controllability of the system are proved. Finally, the numerical solution of the system model is obtained by using MATLAB mathematical software, and the corresponding numerical simulation diagram is given. The results show that the conclusions of numerical calculation and numerical simulation are in accordance with the results of reliability theory, thereby the reliability of the robot safety system is verified.