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Robotics

Explore arXiv robotics papers and cs.RO metadata. Search for robot learning, motion planning and control, then check experiments in the source manuscript.

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At least 145 records · Page 8Linked to original sources

arXiv2023

From the Desks of ROS Maintainers: A Survey of Modern & Capable Mobile Robotics Algorithms in the Robot Operating System 2

The Robot Operating System 2 (ROS 2) is rapidly impacting the intelligent machines sector -- on space missions, large agriculture equipment, multi-robot fleets, and more. Its success derives from its focused design and improved capabilities targeting product-grade and modern robotic systems. Following ROS 2's example, the mobile robotics ecosystem has been fully redesigned based on the transformed needs of modern robots and is experiencing active development not seen since its inception. This paper comes from the desks of the key ROS Navigation maintainers to review and analyze the state of the art of robotics navigation in ROS 2. This includes new systems without parallel in ROS 1 or other similar mobile robotics frameworks. We discuss current research products and historically robust methods that provide differing behaviors and support for most every robot type. This survey consists of overviews, comparisons, and expert insights organized by the fundamental problems in the field. Some of these implementations have yet to be described in literature and many have not been benchmarked relative to others. We end by providing a glimpse into the future of the ROS 2 mobile robotics ecosystem.

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arXiv2024

TalkWithMachines: Enhancing Human-Robot Interaction for Interpretable Industrial Robotics Through Large/Vision Language Models

TalkWithMachines aims to enhance human-robot interaction by contributing to interpretable industrial robotic systems, especially for safety-critical applications. The presented paper investigates recent advancements in Large Language Models (LLMs) and Vision Language Models (VLMs), in combination with robotic perception and control. This integration allows robots to understand and execute commands given in natural language and to perceive their environment through visual and/or descriptive inputs. Moreover, translating the LLM's internal states and reasoning into text that humans can easily understand ensures that operators gain a clearer insight into the robot's current state and intentions, which is essential for effective and safe operation. Our paper outlines four LLM-assisted simulated robotic control workflows, which explore (i) low-level control, (ii) the generation of language-based feedback that describes the robot's internal states, (iii) the use of visual information as additional input, and (iv) the use of robot structure information for generating task plans and feedback, taking the robot's physical capabilities and limitations into account. The proposed concepts are presented in a set of experiments, along with a brief discussion. Project description, videos, and supplementary materials will be available on the project website: https://talk-machines.github.io.

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arXiv2023

Social Robots As Companions for Lonely Hearts: The Role of Anthropomorphism and Robot Appearance

Loneliness is a distressing personal experience and a growing social issue. Social robots could alleviate the pain of loneliness, particularly for those who lack in-person interaction. This paper investigated how the effect of loneliness on the anthropomorphism of social robots differs by robot appearance, and how it influences purchase intention. Participants viewed a video of one of the three robots (machine-like, animal-like, and human-like) moving and interacting with a human counterpart. Bootstrapped multiple regression results revealed that although the unique effect of animal-likeness on anthropomorphism compared to human-likeness was higher, lonely individuals' tendency to anthropomorphize the animal-like robot was lower than that of the human-like robot. This moderating effect remained significant after covariates were included. Bootstrapped mediation analysis showed that anthropomorphism had both a positive direct effect on purchase intent and a positive indirect effect mediated by likability. Our results suggest that lonely individuals' tendency of anthropomorphizing social robots should not be summarized into one unified inclination. Moreover, by extending the effect of loneliness on anthropomorphism to likability and purchase intent, this current study explored the potential of social robots to be adopted as companions of lonely individuals in their real life. Lastly, we discuss the practical implications of the current study for designing social robots.

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arXiv2023

Advantages of Multimodal versus Verbal-Only Robot-to-Human Communication with an Anthropomorphic Robotic Mock Driver

Robots are increasingly used in shared environments with humans, making effective communication a necessity for successful human-robot interaction. In our work, we study a crucial component: active communication of robot intent. Here, we present an anthropomorphic solution where a humanoid robot communicates the intent of its host robot acting as an "Anthropomorphic Robotic Mock Driver" (ARMoD). We evaluate this approach in two experiments in which participants work alongside a mobile robot on various tasks, while the ARMoD communicates a need for human attention, when required, or gives instructions to collaborate on a joint task. The experiments feature two interaction styles of the ARMoD: a verbal-only mode using only speech and a multimodal mode, additionally including robotic gaze and pointing gestures to support communication and register intent in space. Our results show that the multimodal interaction style, including head movements and eye gaze as well as pointing gestures, leads to more natural fixation behavior. Participants naturally identified and fixated longer on the areas relevant for intent communication, and reacted faster to instructions in collaborative tasks. Our research further indicates that the ARMoD intent communication improves engagement and social interaction with mobile robots in workplace settings.

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arXiv2018

Human-Robot Trust Integrated Task Allocation and Symbolic Motion planning for Heterogeneous Multi-robot Systems

This paper presents a human-robot trust integrated task allocation and motion planning framework for multi-robot systems (MRS) in performing a set of tasks concurrently. A set of task specifications in parallel are conjuncted with MRS to synthesize a task allocation automaton. Each transition of the task allocation automaton is associated with the total trust value of human in corresponding robots. Here, the human-robot trust model is constructed with a dynamic Bayesian network (DBN) by considering individual robot performance, safety coefficient, human cognitive workload and overall evaluation of task allocation. Hence, a task allocation path with maximum encoded human-robot trust can be searched based on the current trust value of each robot in the task allocation automaton. Symbolic motion planning (SMP) is implemented for each robot after they obtain the sequence of actions. The task allocation path can be intermittently updated with this DBN based trust model. The overall strategy is demonstrated by a simulation with 5 robots and 3 parallel subtask automata.

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arXiv2020

Robotics Software Engineering: A Perspective from the Service Robotics Domain

Robots that support humans by performing useful tasks (a.k.a., service robots) are booming worldwide. In contrast to industrial robots, the development of service robots comes with severe software engineering challenges, since they require high levels of robustness and autonomy to operate in highly heterogeneous environments. As a domain with critical safety implications, service robotics faces a need for sound software development practices. In this paper, we present the first large-scale empirical study to assess the state of the art and practice of robotics software engineering. We conducted 18 semi-structured interviews with industrial practitioners working in 15 companies from 9 different countries and a survey with 156 respondents (from 26 countries) from the robotics domain. Our results provide a comprehensive picture of (i) the practices applied by robotics industrial and academic practitioners, including processes, paradigms, languages, tools, frameworks, and reuse practices, (ii) the distinguishing characteristics of robotics software engineering, and (iii) recurrent challenges usually faced, together with adopted solutions. The paper concludes by discussing observations, derived hypotheses, and proposed actions for researchers and practitioners.

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arXiv2024

An Open-Source Reproducible Chess Robot for Human-Robot Interaction Research

Recent advancements in AI have accelerated the evolution of versatile robot designs. Chess provides a standardized environment for evaluating the impact of robot behavior on human behavior. This article presents an open-source chess robot for human-robot interaction (HRI) research, specifically focusing on verbal and non-verbal interactions. The OpenChessRobot recognizes chess pieces using computer vision, executes moves, and interacts with the human player through voice and robotic gestures. We detail the software design, provide quantitative evaluations of the efficacy of the robot, and offer a guide for its reproducibility. An online survey examining people's views of the robot in three possible scenarios was conducted with 597 participants. The robot received the highest ratings in the robotics education and the chess coach scenarios, while the home entertainment scenario received the lowest scores. The code is accessible on GitHub: https://github.com/renchizhhhh/OpenChessRobot

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arXiv2024

Uniform vs. Lognormal Kinematics in Robots: Perceptual Preferences for Robotic Movements

Collaborative robots or cobots interact with humans in a common work environment. In cobots, one under investigated but important issue is related to their movement and how it is perceived by humans. This paper tries to analyze whether humans prefer a robot moving in a human or in a robotic fashion. To this end, the present work lays out what differentiates the movement performed by an industrial robotic arm from that performed by a human one. The main difference lies in the fact that the robotic movement has a trapezoidal speed profile, while for the human arm, the speed profile is bell-shaped and during complex movements, it can be considered as a sum of superimposed bell-shaped movements. Based on the lognormality principle, a procedure was developed for a robotic arm to perform human-like movements. Both speed profiles were implemented in two industrial robots, namely, an ABB IRB 120 and a Universal Robot UR3. Three tests were used to study the subjects' preference when seeing both movements and another analyzed the same when interacting with the robot by touching its ends with their fingers.

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arXiv2012

Study of the Importance of Adequacy to Robot Verbal and Non Verbal Communication in Human-Robot interaction

The Robadom project aims at creating a homecare robot that help and assist people in their daily life, either in doing task for the human or in managing day organization. A robot could have this kind of role only if it is accepted by humans. Before thinking about the robot appearance, we decided to evaluate the importance of the relation between verbal and nonverbal communication during a human-robot interaction in order to determine the situation where the robot is accepted. We realized two experiments in order to study this acceptance. The first experiment studied the importance of having robot nonverbal behavior in relation of its verbal behavior. The second experiment studied the capability of a robot to provide a correct human-robot interaction.

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arXiv2015

To Make a Robot Secure: An Experimental Analysis of Cyber Security Threats Against Teleoperated Surgical Robots

Teleoperated robots are playing an increasingly important role in military actions and medical services. In the future, remotely operated surgical robots will likely be used in more scenarios such as battlefields and emergency response. But rapidly growing applications of teleoperated surgery raise the question; what if the computer systems for these robots are attacked, taken over and even turned into weapons? Our work seeks to answer this question by systematically analyzing possible cyber security attacks against Raven II, an advanced teleoperated robotic surgery system. We identify a slew of possible cyber security threats, and experimentally evaluate their scopes and impacts. We demonstrate the ability to maliciously control a wide range of robots functions, and even to completely ignore or override command inputs from the surgeon. We further find that it is possible to abuse the robot's existing emergency stop (E-stop) mechanism to execute efficient (single packet) attacks. We then consider steps to mitigate these identified attacks, and experimentally evaluate the feasibility of applying the existing security solutions against these threats. The broader goal of our paper, however, is to raise awareness and increase understanding of these emerging threats. We anticipate that the majority of attacks against telerobotic surgery will also be relevant to other teleoperated robotic and co-robotic systems.

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arXiv2017

This robot stinks! Differences between perceived mistreatment of robot and computer partners

Robots (and computers) are increasingly being used in scenarios where they interact socially with people. How people react to these agents is telling about the perceived animacy of such agents. Mistreatment of robots (or computers) by co-workers might provoke such telling reactions. The purpose of this study was to discover if people perceived mistreatment directed towards a robot any differently than toward a computer. This will provide some understanding of how people perceive robots in collaborative social settings. We conducted a between-subjects study with 80 participants. Participants worked cooperatively with either a robot or a computer which acted as the "recorder" for the group. A confederate either acted aggressively or neutrally towards the "recorder." We hypothesized that people would not socially accept mistreatment towards an agent that they felt was intelligent and similar to themselves; that participants would perceive the robot as more similar in appearance and emotional capability to themselves than a computer; and would observe more mistreatment. The final results supported our hypothesis; the participants observed mistreatment in the robot, but not the computer. Participants felt significantly more sympathetic towards the robot and also believed that it was much more emotionally capable.

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arXiv2018

Robot_gym: accelerated robot training through simulation in the cloud with ROS and Gazebo

Rather than programming, training allows robots to achieve behaviors that generalize better and are capable to respond to real-world needs. However, such training requires a big amount of experimentation which is not always feasible for a physical robot. In this work, we present robot_gym, a framework to accelerate robot training through simulation in the cloud that makes use of roboticists' tools, simplifying the development and deployment processes on real robots. We unveil that, for simple tasks, simple 3DoF robots require more than 140 attempts to learn. For more complex, 6DoF robots, the number of attempts increases to more than 900 for the same task. We demonstrate that our framework, for simple tasks, accelerates the robot training time by more than 33% while maintaining similar levels of accuracy and repeatability.

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arXiv2018

SERoCS: Safe and Efficient Robot Collaborative Systems for Next Generation Intelligent Industrial Co-Robots

Human-robot collaborations have been recognized as an essential component for future factories. It remains challenging to properly design the behavior of those co-robots. Those robots operate in dynamic uncertain environment with limited computation capacity. The design objective is to maximize their task efficiency while guaranteeing safety. This paper discusses a set of design principles of a safe and efficient robot collaboration system (SERoCS) for the next generation co-robots, which consists of robust cognition algorithms for environment monitoring, efficient task planning algorithms for reference generations, and safe motion planning and control algorithms for safe human-robot interactions. The proposed SERoCS will address the design challenges and significantly expand the skill sets of the co-robots to allow them to work safely and efficiently with their human counterparts. The development of SERoCS will create a significant advancement toward adoption of co-robots in various industries. The experiments validate the effectiveness of SERoCS.

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arXiv2019

Robots as Actors in a Film: No War, A Robot Story

Will the Third World War be fought by robots? This short film is a light-hearted comedy that aims to trigger an interesting discussion and reflexion on the terrifying killer-robot stories that increasingly fill us with dread when we read the news headlines. The fictional scenario takes inspiration from current scientific research and describes a future where robots are asked by humans to join the war. Robots are divided, sparking protests in robot society... will robots join the conflict or will they refuse to be employed in human warfare? Food for thought for engineers, roboticists and anyone imagining what the upcoming robot revolution could look like. We let robots pop on camera to tell a story, taking on the role of actors playing in the film, instructed through code on how to "act" for each scene.

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arXiv2020

Co-Robots as Care Robots

Cooperation and collaboration robots, co-robots or cobots for short, are an integral part of factories. For example, they work closely with the fitters in the automotive sector, and everyone does what they do best. However, the novel robots are not only relevant in production and logistics, but also in the service sector, especially where proximity between them and the users is desired or unavoidable. For decades, individual solutions of a very different kind have been developed in care. Now experts are increasingly relying on co-robots and teaching them the special tasks that are involved in care or therapy. This article presents the advantages, but also the disadvantages of co-robots in care and support, and provides information with regard to human-robot interaction and communication. The article is based on a model that has already been tested in various nursing and retirement homes, namely Lio from F&P Robotics, and uses results from accompanying studies. The authors can show that co-robots are ideal for care and support in many ways. Of course, it is also important to consider a few points in order to guarantee functionality and acceptance.

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arXiv2021

External Human-Machine Interface on Delivery Robots: Expression of Navigation Intent of the Robot

External Human-Machine Interfaces (eHMI) are widely used on robots and autonomous vehicles to convey the machine's intent to humans. Delivery robots are getting common, and they share the sidewalk along with the pedestrians. Current research has explored the design of eHMI and its effectiveness for social robots and autonomous vehicles, but the use of eHMIs on delivery robots still remains unexplored. There is a knowledge gap on the effective use of eHMIs on delivery robots for indicating the robot's navigational intent to the pedestrians. An online survey with 152 participants was conducted to investigate the comprehensibility of the display and light-based eHMIs that convey the delivery robot's navigational intent under common navigation scenarios. Results show that display is preferred over lights in conveying the intent. The preferred type of content to be displayed varies according to the scenarios. Additionally, light is preferred as an auxiliary eHMI to present redundant information. The findings of this study can contribute to the development of future designs of eHMI on delivery robots.

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arXiv2022

Robot's Gendering Trouble: A Scoping Review of Gendering Humanoid Robots and its Effects on HRI

The discussion around the problematic practice of gendering humanoid robots has risen to the foreground in the last few years. To lay the basis for a thorough understanding of how robot's "gender" has been understood within the Human-Robot Interaction (HRI) community - i.e., how it has been manipulated, in which contexts, and which effects it has yield on people's perceptions and interactions with robots - we performed a scoping review of the literature. We identified 553 papers relevant for our review retrieved from 5 different databases. The final sample of reviewed papers included 35 papers written between 2005 and 2021, which involved a total of 3902 participants. In this article, we thoroughly summarize these papers by reporting information about their objectives and assumptions on gender (i.e., definitions and reasons to manipulate gender), their manipulation of robot's "gender" (i.e., gender cues and manipulation checks), their experimental designs (e.g., demographics of participants, employed robots), and their results (i.e., main and interaction effects). The review reveals that robot's "gender" does not affect crucial constructs for the HRI, such as likability and acceptance, but rather bears its strongest effect on stereotyping. We leverage our different epistemological backgrounds in Social Robotics and Gender Studies to provide a comprehensive interdisciplinary perspective on the results of the review and suggest ways to move forward in the field of HRI.

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arXiv2022

The Effect of Robot Posture and Idle Motion on Spontaneous Emotional Contagion during Robot-Human Interactions

In the next decade, social robots will be implemented in many public spaces to provide services to humans. We question the properties of these social robots to afford acceptance and spontaneous emotional interactions. More specifically, in the present study, we report the effects of idle motion frequency in a robot on emotional contagion in a face-to-face interactive task with a human participant. The robotic system Buddy was programmed to adopt a sad posture and facial expression while telling three sad stories and moving its head up/down at low, medium, and high frequency. Each participant (N=15 total) was invited to sit in front of Buddy and listen to the stories. Unconscious changes in posture in the human participant were recorded using a 3D motion capture system (Qualysis). Results show greater inclinations of the shoulder/torso towards the ground in low-frequency trials and more rigid postures in high-frequency trials. The quantity of spontaneous movement was also greater when Buddy moved at slow frequencies. These findings echo results reported in experimental psychology when two individuals are engaged in social interactions. The scores obtained in the Godspeed questionnaire further suggest that emotional contagion may occur when Buddy moves slowly because the robotic system is perceived as more natural and knowledgeable, e.g., at speed coherent with the expressed emotion. Our work explores the importance of body posture and frequency of idle motion in the conception of robotic systems. Such additions could provide social robots that afford emotional contagion in effortless robot-human collaborative tasks.

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