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Robotics

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arXiv2019

A Review of Soft Robots

Traditional robots have rigid links and structures that limit their ability to interact with the dynamics of their immediate environment. For example, conventional robot manipulators with rigid links can only manipulate objects using specific end effectors. These robots often encounter difficulties operating in unstructured and highly congested environments. A variety of biological organisms exhibit complex movement with soft structures devoid of rigid components. Inspired by biology, researchers have been able to design and build soft robots. With a soft structure and redundant degrees of freedom, these robots can be used for delicate tasks in unstructured environments. This review discusses the motivation for soft robots, their design processes as well as their applications and limitations. Soft robots have the ability to operate in unstructured environment due to their inherent potential to exploit morphological computation to adapt to, and interact with, the world in a way that is difficult with rigid systems. Soft robots could be used for operations, ranging from search and rescue operations in a natural disaster relief effort, and of emerging interest is in the field of medical care as seen in personal robots.

cs.RO↗

arXiv2019

Towards Robotic Things in Society

Emerging are so-called smart things embedded with computational, sensing, networking and actuation capabilities, from smart bins to smart park benches, as well as the proliferation of autonomous vehicles and robots in an increasingly wide range of applications. This is not only an increased in automation affecting and hopefully improving daily life, but also calls for thinking about what a society saturated with such robotic things (i.e., smart things and robots) might look like. This paper discusses five aspects of a vision of Internet connected robotic things (or Internet of Robotic Things (IoRT)) occupying and operating in public spaces, from streets, parks to shopping malls. We discuss, highlighting issues, with the notion of an entourage of drones and robots accompanying people in public places, the idea of creating environments or envelopes suitable for robot function, the idea of societies of robotic things, and governance for robotic things in public spaces.

cs.CY↗

arXiv2019

Human Whole-Body Dynamics Estimation for Enhancing Physical Human-Robot Interaction

In the last two decades the scientific community has shown a great interest in understanding and shaping the interaction mechanisms between humans and robots. The interaction implies communication between two dyadic agents and, if the type of interaction is physical, the communication is represented by the set of forces exchanged during the interaction. Within this context, the role of quantifying these forces becomes of pivotal importance for understanding the interaction mechanisms. At the current scientific stage, classical robots are built to act for humans, but the scientific demand is going towards the direction of robots that will have to collaborate with humans. This will be possible by providing the robots with sufficient pieces of information of the agent they are interacting with (i.e., kinematic and dynamic model of the human). In a modern age where humans need the help of robots, apparently in an opposite trend, this thesis attempts to answer the following questions: Do robots need humans? Should robots know their human partners? A tentative answer is provided here in the form of a novel framework for the simultaneous human whole-body motion tracking and dynamics estimation, in a real-time scenario. The framework encompasses a set of body-mounted sensors and a probabilistic algorithm able of estimating physical quantities that in humans are not directly measurable (i.e., torques and internal forces). This thesis is mainly focussed on the paramount role in retrieving the human dynamics estimation but straightforwardly it leaves the door open to the next development step: passing the human dynamics feedback to the robot controllers. This step will enable the robot with the capability to observe and understand the human partner by generating an enhanced (intentional) interaction.

cs.RO↗

arXiv2020

A Versatile Multi-Robot Monte Carlo Tree Search Planner for On-Line Coverage Path Planning

Mobile robots hold great promise in reducing the need for humans to perform jobs such as vacuuming, seeding,harvesting, painting, search and rescue, and inspection. In practice, these tasks must often be done without an exact map of the area and could be completed more quickly through the use of multiple robots working together. The task of simultaneously covering and mapping an area with multiple robots is known as multi-robot on-line coverage and is a growing area of research. Many multi-robot on-line coverage path planning algorithms have been developed as extensions of well established off-line coverage algorithms. In this work we introduce a novel approach to multi-robot on-line coverage path planning based on a method borrowed from game theory and machine learning- Monte Carlo Tree Search. We implement a Monte Carlo Tree Search planner and compare completion times against a Boustrophedon-based on-line multi-robot planner. The MCTS planner is shown to perform on par with the conventional Boustrophedon algorithm in simulations varying the number of robots and the density of obstacles in the map. The versatility of the MCTS planner is demonstrated by incorporating secondary objectives such as turn minimization while performing the same coverage task. The versatility of the MCTS planner suggests it is well suited to many multi-objective tasks that arise in mobile robotics.

cs.MA↗

arXiv2020

Enabling Human-Robot Collaboration via Holistic Human Perception and Partner-Aware Control

As robotic technology advances, the barriers to the coexistence of humans and robots are slowly coming down. Application domains like elderly care, collaborative manufacturing, collaborative manipulation, etc., are considered the need of the hour, and progress in robotics holds the potential to address many societal challenges. The future socio-technical systems constitute of blended workforce with a symbiotic relationship between human and robot partners working collaboratively. This thesis attempts to address some of the research challenges in enabling human-robot collaboration. In particular, the challenge of a holistic perception of a human partner to continuously communicate his intentions and needs in real-time to a robot partner is crucial for the successful realization of a collaborative task. Towards that end, we present a holistic human perception framework for real-time monitoring of whole-body human motion and dynamics. On the other hand, the challenge of leveraging assistance from a human partner will lead to improved human-robot collaboration. In this direction, we attempt at methodically defining what constitutes assistance from a human partner and propose partner-aware robot control strategies to endow robots with the capacity to meaningfully engage in a collaborative task.

cs.RO↗

arXiv2020

SIGVerse: A cloud-based VR platform for research on social and embodied human-robot interaction

Common sense and social interaction related to daily-life environments are considerably important for autonomous robots, which support human activities. One of the practical approaches for acquiring such social interaction skills and semantic information as common sense in human activity is the application of recent machine learning techniques. Although recent machine learning techniques have been successful in realizing automatic manipulation and driving tasks, it is difficult to use these techniques in applications that require human-robot interaction experience. Humans have to perform several times over a long term to show embodied and social interaction behaviors to robots or learning systems. To address this problem, we propose a cloud-based immersive virtual reality (VR) platform which enables virtual human-robot interaction to collect the social and embodied knowledge of human activities in a variety of situations. To realize the flexible and reusable system, we develop a real-time bridging mechanism between ROS and Unity, which is one of the standard platforms for developing VR applications. We apply the proposed system to a robot competition field named RoboCup@Home to confirm the feasibility of the system in a realistic human-robot interaction scenario. Through demonstration experiments at the competition, we show the usefulness and potential of the system for the development and evaluation of social intelligence through human-robot interaction. The proposed VR platform enables robot systems to collect social experiences with several users in a short time. The platform also contributes in providing a dataset of social behaviors, which would be a key aspect for intelligent service robots to acquire social interaction skills based on machine learning techniques.

cs.RO↗

arXiv2020

I can attend a meeting too! Towards a human-like telepresence avatar robot to attend meeting on your behalf

Telepresence robots are used in various forms in various use-cases that helps to avoid physical human presence at the scene of action. In this work, we focus on a telepresence robot that can be used to attend a meeting remotely with a group of people. Unlike a one-to-one meeting, participants in a group meeting can be located at a different part of the room, especially in an informal setup. As a result, all of them may not be at the viewing angle of the robot, a.k.a. the remote participant. In such a case, to provide a better meeting experience, the robot should localize the speaker and bring the speaker at the center of the viewing angle. Though sound source localization can easily be done using a microphone-array, bringing the speaker or set of speakers at the viewing angle is not a trivial task. First of all, the robot should react only to a human voice, but not to the random noises. Secondly, if there are multiple speakers, to whom the robot should face or should it rotate continuously with every new speaker? Lastly, most robotic platforms are resource-constrained and to achieve a real-time response, i.e., avoiding network delay, all the algorithms should be implemented within the robot itself. This article presents a study and implementation of an attention shifting scheme in a telepresence meeting scenario which best suits the needs and expectations of the collocated and remote attendees. We define a policy to decide when a robot should rotate and how much based on real-time speaker localization. Using user satisfaction study, we show the efficacy and usability of our system in the meeting scenario. Moreover, our system can be easily adapted to other scenarios where multiple people are located.

cs.RO↗

arXiv2020

A Three-limb Teleoperated Robotic System with Foot Control for Flexible Endoscopic Surgery

Flexible endoscopy requires high skills to manipulate both the endoscope and associated instruments. In most robotic flexible endoscopic systems, the endoscope and instruments are controlled separately by two operators, which may result in communication errors and inefficient operation. We present a novel teleoperation robotic endoscopic system that can be commanded by a surgeon alone. This 13 degrees-of-freedom (DoF) system integrates a foot-controlled robotic flexible endoscope and two hand-controlled robotic endoscopic instruments (a robotic grasper and a robotic cauterizing hook). A foot-controlled human-machine interface maps the natural foot gestures to the 4-DoF movements of the endoscope, and two hand-controlled interfaces map the movements of the two hands to the two instruments individually. The proposed robotic system was validated in an ex-vivo experiment carried out by six subjects, where foot control was also compared with a sequential clutch-based hand control scheme. The participants could successfully teleoperate the endoscope and the two instruments to cut the tissues at scattered target areas in a porcine stomach. Foot control yielded 43.7% faster task completion and required less mental effort as compared to the clutch-based hand control scheme. The system introduced in this paper is intuitive for three-limb manipulation even for operators without experience of handling the endoscope and robotic instruments. This three-limb teleoperated robotic system enables one surgeon to intuitively control three endoscopic tools which normally require two operators, leading to reduced manpower, less communication errors, and improved efficiency.

cs.RO↗

arXiv2020

Collaborative Multi-Robot Systems for Search and Rescue: Coordination and Perception

Autonomous or teleoperated robots have been playing increasingly important roles in civil applications in recent years. Across the different civil domains where robots can support human operators, one of the areas where they can have more impact is in search and rescue (SAR) operations. In particular, multi-robot systems have the potential to significantly improve the efficiency of SAR personnel with faster search of victims, initial assessment and mapping of the environment, real-time monitoring and surveillance of SAR operations, or establishing emergency communication networks, among other possibilities. SAR operations encompass a wide variety of environments and situations, and therefore heterogeneous and collaborative multi-robot systems can provide the most advantages. In this paper, we review and analyze the existing approaches to multi-robot SAR support, from an algorithmic perspective and putting an emphasis on the methods enabling collaboration among the robots as well as advanced perception through machine vision and multi-agent active perception. Furthermore, we put these algorithms in the context of the different challenges and constraints that various types of robots (ground, aerial, surface or underwater) encounter in different SAR environments (maritime, urban, wilderness or other post-disaster scenarios). This is, to the best of our knowledge, the first review considering heterogeneous SAR robots across different environments, while giving two complimentary points of view: control mechanisms and machine perception. Based on our review of the state-of-the-art, we discuss the main open research questions, and outline our insights on the current approaches that have potential to improve the real-world performance of multi-robot SAR systems.

cs.RO↗

arXiv2020

Co-Evolution of Multi-Robot Controllers and Task Cues for Off-World Open Pit Mining

Robots are ideal for open-pit mining on the Moon as its a dull, dirty, and dangerous task. The challenge is to scale up productivity with an ever-increasing number of robots. This paper presents a novel method for developing scalable controllers for use in multi-robot excavation and site-preparation scenarios. The controller starts with a blank slate and does not require human-authored operations scripts nor detailed modeling of the kinematics and dynamics of the excavator. The 'Artificial Neural Tissue' (ANT) architecture is used as a control system for autonomous robot teams to perform resource gathering. This control architecture combines a variable-topology neural-network structure with a coarse-coding strategy that permits specialized areas to develop in the tissue. Our work in this field shows that fleets of autonomous decentralized robots have an optimal operating density. Too few robots result in insufficient labor, while too many robots cause antagonism, where the robots undo each other's work and are stuck in gridlock. In this paper, we explore the use of templates and task cues to improve group performance further and minimize antagonism. Our results show light beacons and task cues are effective in sparking new and innovative solutions at improving robot performance when placed under stressful situations such as severe time-constraint.

cs.RO↗

arXiv2020

Blockchain for Multi-Robot Collaboration to Combat COVID-19 and Future Pandemics

This conceptual paper overviews how blockchain technology is involving the operation of multi-robot collaboration for combating COVID-19 and future pandemics. Robots are a promising technology for providing many tasks such as spraying, disinfection, cleaning, treating, detecting high body temperature/mask absence, and delivering goods and medical supplies experiencing an epidemic COVID-19. For combating COVID-19, many heterogeneous and homogenous robots are required to perform different tasks for supporting different purposes in the quarantine area. Controlling and decentralizing multi-robot play a vital role in combating COVID-19 by reducing human interaction, monitoring, delivering goods. Blockchain technology can manage multi-robot collaboration in a decentralized fashion, improve the interaction among them to exchange information, share representation, share goals, and trust. We highlight the challenges and provide the tactical solutions enabled by integrating blockchain and multi-robot collaboration to combat COVID-19 pandemic. The framework of our conceptual proposed can increase the intelligence, decentralization, and autonomous operations of connected multi-robot collaboration in the blockchain network. We overview blockchain potential benefits to defining a framework of multi-robot collaboration applications to combat COVID-19 epidemics such as monitoring and outdoor and hospital End to End (E2E) delivery systems. Furthermore, we discuss the challenges and opportunities of integrated blockchain, multi-robot collaboration, and the Internet of Things (IoT) for combating COVID-19 and future pandemics.

cs.RO↗

arXiv2021

Pattern Formation by Robots with Inaccurate Movements

\textsc{Arbitrary Pattern Formation} is a fundamental problem in autonomous mobile robot systems. The problem asks to design a distributed algorithm that moves a team of autonomous, anonymous and identical mobile robots to form any arbitrary pattern $F$ given as input. In this paper, we study the problem for robots whose movements can be inaccurate. Our movement model assumes errors in both direction and extent of the intended movement. Forming the given pattern exactly is not possible in this setting. So we require that the robots must form a configuration which is close to the given pattern $F$. We call this the \textsc{Approximate Arbitrary Pattern Formation} problem. We show that with no agreement in coordinate system, the problem is unsolvable, even by fully synchronous robots, if the initial configuration 1) has rotational symmetry and there is no robot at the center of rotation or 2) has reflectional symmetry and there is no robot on the reflection axis. From all other initial configurations, we solve the problem by 1) oblivious, silent and semi-synchronous robots and 2) oblivious, asynchronous robots that can communicate using externally visible lights.

cs.DC↗

arXiv2020

A Comparison Between Joint Space and Task Space Mappings for Dynamic Teleoperation of an Anthropomorphic Robotic Arm in Reaction Tests

Teleoperation (i.e., controlling a robot with human motion) proves promising in enabling a humanoid robot to move as dynamically as a human. But how to map human motion to a humanoid robot matters because a human and a humanoid robot rarely have identical topologies and dimensions. This work presents an experimental study that utilizes reaction tests to compare the proposed joint space mapping and the proposed task space mapping for dynamic teleoperation of an anthropomorphic robotic arm that possesses human-level dynamic motion capabilities. The experimental results suggest that the robot achieved similar and, in some cases, human-level dynamic performances with both mappings for the six participating human subjects. All subjects became proficient at teleoperating the robot with both mappings after practice, despite that the subjects and the robot differed in size and link length ratio and that the teleoperation required the subjects to move unintuitively. Yet, most subjects developed their teleoperation proficiencies more quickly with the task space mapping than with the joint space mapping after similar amounts of practice. This study also indicates the potential values of a three-dimensional task space mapping, a teleoperation training simulator, and force feedback to the human pilot for intuitive and dynamic teleoperation of a humanoid robot's arms.

cs.RO↗

arXiv2020

Why robots should be technical: Correcting mental models through technical architecture concepts

Research in social robotics is commonly focused on designing robots that imitate human behavior. While this might increase a user's satisfaction and acceptance of robots at first glance, it does not automatically aid a non-expert user in naturally interacting with robots, and might actually hurt their ability to correctly anticipate a robot's capabilities. We argue that a faulty mental model, that the user has of the robot, is one of the main sources of confusion. In this work we investigate how communicating technical concepts of robotic systems to users affects their mental models, and how this can increase the quality of human-robot interaction. We conducted an online study and investigated possible ways of improving users' mental models. Our results underline that communicating technical concepts can form an improved mental model. Consequently, we show the importance of consciously designing robots that express their capabilities and limitations.

cs.RO↗

arXiv2020

Uniform Scattering of Robots on Alternate Nodes of a Grid

In this paper, we propose a distributed algorithm to uniformly scatter the robots along a grid, with robots on alternate nodes of this grid distribution. These homogeneous, autonomous mobile robots place themselves equidistant apart on the grid, which can be required for guarding or covering a geographical area by the robots. The robots operate by executing cycles of the states "look-compute-move". In the look phase, it looks to see the position of the other robots; in the compute phase, it computes a destination to move to; and then in the move phase, it moves to that computed destination. They do not interact by message passing and can recollect neither the past actions nor the looked data from the previous cycle, i.e., oblivious. The robots are semi-synchronous, anonymous and have unlimited visibility. Eventually, the robots uniformly distribute themselves on alternate nodes of a grid, leaving the adjacent nodes of the grid vacant. The algorithm presented also assures no collision or deadlock among the robots.

cs.RO↗

arXiv2021

Predictive Processing in Cognitive Robotics: a Review

Predictive processing has become an influential framework in cognitive sciences. This framework turns the traditional view of perception upside down, claiming that the main flow of information processing is realized in a top-down hierarchical manner. Furthermore, it aims at unifying perception, cognition, and action as a single inferential process. However, in the related literature, the predictive processing framework and its associated schemes such as predictive coding, active inference, perceptual inference, free-energy principle, tend to be used interchangeably. In the field of cognitive robotics there is no clear-cut distinction on which schemes have been implemented and under which assumptions. In this paper, working definitions are set with the main aim of analyzing the state of the art in cognitive robotics research working under the predictive processing framework as well as some related non-robotic models. The analysis suggests that, first, both research in cognitive robotics implementations and non-robotic models needs to be extended to the study of how multiple exteroceptive modalities can be integrated into prediction error minimization schemes. Second, a relevant distinction found here is that cognitive robotics implementations tend to emphasize the learning of a generative model, while in non-robotics models it is almost absent. Third, despite the relevance for active inference, few cognitive robotics implementations examine the issues around control and whether it should result from the substitution of inverse models with proprioceptive predictions. Finally, limited attention has been placed on precision weighting and the tracking of prediction error dynamics. These mechanisms should help to explore more complex behaviors and tasks in cognitive robotics research under the predictive processing framework.

cs.RO↗

arXiv2021

A Dual-arm Robot that Autonomously Lifts Up and Tumbles Heavy Plates Using Crane Pulley Blocks

This paper develops a planner that plans the action sequences and motion for a dual-arm robot to lift up and flip heavy plates using crane pulley blocks. The problem is motivated by the low payload of modern collaborative robots. Instead of directly manipulating heavy plates that collaborative robots cannot afford, the paper develops a planner for collaborative robots to operate crane pulley blocks. The planner assumes a target plate is pre-attached to the crane hook. It optimizes dual-arm action sequences and plans the robot's dual-arm motion that pulls the rope of the crane pulley blocks to lift up the plate. The crane pulley blocks reduce the payload that each robotic arm needs to bear. When the plate is lifted up to a satisfying pose, the planner plans a pushing motion for one of the robot arms to tumble over the plate while considering force and moment constraints. The article presents the technical details of the planner and several experiments and analysis carried out using a dual-arm robot made by two Universal Robots UR3 arms. The influence of various parameters and optimization goals are investigated and compared in depth. The results show that the proposed planner is flexible and efficient.

cs.RO↗

arXiv2021

Acoustic Communication and Sensing for Inflatable Modular Soft Robots

Modular soft robots combine the strengths of two traditionally separate areas of robotics. As modular robots, they can show robustness to individual failure and reconfigurability; as soft robots, they can deform and undergo large shape changes in order to adapt to their environment, and have inherent human safety. However, for sensing and communication these robots also combine the challenges of both: they require solutions that are scalable (low cost and complexity) and efficient (low power) to enable collectives of large numbers of robots, and these solutions must also be able to interface with the high extension ratio elastic bodies of soft robots. In this work, we seek to address these challenges using acoustic signals produced by piezoelectric surface transducers that are cheap, simple, and low power, and that not only integrate with but also leverage the elastic robot skins for signal transmission. Importantly, to further increase scalability, the transducers exhibit multi-functionality made possible by a relatively flat frequency response across the audible and ultrasonic ranges. With minimal hardware, they enable directional contact-based communication, audible-range communication at a distance, and exteroceptive sensing. We demonstrate a subset of the decentralized collective behaviors these functions make possible with multi-robot hardware implementations. The use of acoustic waves in this domain is shown to provide distinct advantages over existing solutions.

cs.RO↗