Challenges in Collaborative HRI for Remote Robot Teams

Collaboration between human supervisors and remote teams of robots is highly challenging, particularly in high-stakes, distant, hazardous locations, such as off-shore energy platforms. In order for these teams of robots to truly be beneficial, they need to be trusted to operate autonomously, performing tasks such as inspection and emergency response, thus reducing the number of personnel placed in harm's way. As remote robots are generally trusted less than robots in close-proximity, we present a solution to instil trust in the operator through a `mediator robot' that can exhibit social skills, alongside sophisticated visualisation techniques. In this position paper, we present general challenges and then take a closer look at one challenge in particular, discussing an initial study, which investigates the relationship between the level of control the supervisor hands over to the mediator robot and how this affects their trust. We show that the supervisor is more likely to have higher trust overall if their initial experience involves handing over control of the emergency situation to the robotic assistant. We discuss this result, here, as well as other challenges and interaction techniques for human-robot collaboration.Comment: 9 pages. Peer reviewed position paper accepted in the CHI 2019 Workshop: The Challenges of Working on Social Robots that Collaborate with People (SIRCHI2019), ACM CHI Conference on Human Factors in Computing Systems, May 2019, Glasgow, U

Spatio-Temporal Avoidance of Predicted Occupancy in Human-Robot Collaboration

This paper addresses human-robot collaboration (HRC) challenges of integrating predictions of human activity to provide a proactive-n-reactive response capability for the robot. Prior works that consider current or predicted human poses as static obstacles are too nearsighted or too conservative in planning, potentially causing delayed robot paths. Alternatively, time-varying prediction of human poses would enable robot paths that avoid anticipated human poses, synchronized dynamically in time and space. Herein, a proactive path planning method, denoted STAP, is presented that uses spatiotemporal human occupancy maps to find robot trajectories that anticipate human movements, allowing robot passage without stopping. In addition, STAP anticipates delays from robot speed restrictions required by ISO/TS 15066 speed and separation monitoring (SSM). STAP also proposes a sampling-based planning algorithm based on RRT* to solve the spatio-temporal motion planning problem and find paths of minimum expected duration. Experimental results show STAP generates paths of shorter duration and greater average robot-human separation distance throughout tasks. Additionally, STAP more accurately estimates robot trajectory durations in HRC, which are useful in arriving at proactive-n-reactive robot sequencing.Comment: 7 pages, 7 figures. Accepted at IEEE ROMAN 202

Safe human-robot interaction based on dynamic sphere-swept line bounding volumes

This paper presents a geometric representation for human operators and robotic manipulators, which cooperate in the development of flexible tasks. The main goal of this representation is the implementation of real-time proximity queries, which are used by safety strategies for avoiding dangerous collisions between humans and robotic manipulators. This representation is composed of a set of bounding volumes based on swept-sphere line primitives, which encapsulate their links more precisely than previous sphere-based models. The radius of each bounding volume does not only represent the size of the encapsulated link, but it also includes an estimation of its motion. The radii of these dynamic bounding volumes are obtained from an algorithm which computes the linear velocity of each link. This algorithm has been implemented for the development of a safety strategy in a real human–robot interaction task.This work is funded by the Spanish Ministry of Education and the Spanish Ministry of Science and Innovation through the projects DPI2005-06222 and DPI2008-02647 and the grant AP2005-1458

Robotic Automation of Turning Machines in Fenceless Production: A Planning Toolset for Economic-based Selection Optimization between Collaborative and Classical Industrial Robots

Ursprünglich wurden Industrieroboter hauptsächlich hinter Schutzzäunen betrieben, um den Sicherheitsanforderungen gerecht zu werden. Mit der Flexibilisierung der Produktion wurden diese scharfen Trennbereiche zunehmend aufgeweicht und externe Sicherheitstechnik, wie Abstandssensoren, genutzt, um Industrieroboter schutzzaunlos zu betreiben. Ausgehend vom Gedanken dieser Koexistenz bzw. Kooperation wurde die Sicherheitssensorik in den Roboter integriert, um eine wirkliche Kollaboration zu ermöglichen. Diese sogenannten kollaborierenden Roboter, oder Cobots, eröffnen neue Applikationsfelder und füllen somit die bestehenden Automatisierungslücken. Doch welche Automatisierungsvariante ist aus wirtschaftlichen Gesichtspunkten die geeignetste? Bisherige Forschung untersucht zum Großteil isoliert eine der beiden Technologien, ohne dabei einen Systemvergleich hinsichtlich technologischer Spezifika und Wirtschaftlichkeit anzustellen. Daher widmet sich diese Dissertation einer Methodik zum wirtschaftlichen Vergleich von kollaborierenden Robotern und Industrierobotern in schutzzaunlosen Maschinenbeladungssystemen. Besonderer Fokus liegt dabei auf dem Herausarbeiten der technischen Faktoren, die die Wirtschaftlichkeit maßgeblich beeinflussen, um ein Systemverständnis der wirtschaftlichen Struktur beider Robotertechnologievarianten zu erhalten. Zur Untersuchung werden die Inhalte eines solchen Planungsvorhabens beschrieben, kategorisiert, systematisiert und modularisiert. Auf wirtschaftlicher Seite wird ein geeignetes Optimierungsmodell vorgestellt, während auf technischer Seite vor allem die Machbarkeit hinsichtlich Greifbarkeit, Layoutplanung, Robotergeschwindigkeiten und Zykluszeitbestimmung untersucht wird. Mit deduktiven, simulativen, empirischen und statistischen Methoden wird das Systemverhalten für die einzelnen Planungsinhalte analysiert, um die Gesamtwirtschaftlichkeit mit einem Minimum an Investment,- Produktions,- und Zykluszeitinformationen a priori vorhersagen zu können. Es wird gezeigt, dass durch einen Reverse Engineering Ansatz die notwendigen Planungsdaten, im Sinne von Layoutkomposition, Robotergeschwindigkeiten und Taktzeiten, mithilfe von Frontloading zu Planungsbeginn zur Verfügung gestellt werden können. Dabei dient der Kapitalwert als wirtschaftliche Bewertungsgrundlage, dessen Abhängigkeit vom Mensch-Roboter-Interaktionsgrad in einem Vorteilhaftigkeitsdiagramm für die einzelnen Technologiealternativen dargestellt werden kann. Wirtschaftlich fundierte Entscheidungen können somit auf quantitiativer Basis getroffen werden.:1. Introduction 25 1.1 Research Domain 25 1.2 Research Niche 26 1.3 Research Structure 28 2. State of the Art and Research 31 2.1 Turning Machines and Machine Tending 31 2.1.1 Tooling Machine Market Trends and Machine Tending Systems 31 2.1.2 Workpiece System 34 2.1.3 Machine System 36 2.1.4 Logistics System 39 2.1.5 Handling System 41 2.2 Robotics 43 2.2.1 Robot Installation Development and Application Fields 43 2.2.2 Fenceless Industrial and Collaborative Robots 48 2.2.3 Robot Grippers 55 2.3 Planning and Evaluation Methods 56 2.3.1 Planning of General and Manual Workstations 56 2.3.2 Cell Planning for Fully Automated and Hybrid Robot Systems 59 2.3.3 Robot Safety Planning 61 2.3.4 Economic Evaluation Methods 70 2.4 Synthesis - State of the Art and Research 71 3. Solution Approach 77 3.1 Need for Research and General Solution Approach 77 3.2 Use Case Delineation and Planning Focus 80 3.3 Economic Module – Solution Approach 86 3.4 Gripper Feasibility Module – Solution Approach 89 3.5 Rough Layout Discretization Model – Solution Approach 94 3.6 Cycle Time Estimation Module – Solution Approach 97 3.7 Collaborative Speed Estimation Module – Solution Approach 103 3.7.1 General Approach 103 3.7.2 Case 1: Quasi-static Contact with Hand 107 3.7.3 Case 2: Transient Contact with Hand 109 3.7.4 Case 3: Transient Contact with Shoulder 111 3.8 Synthesis – Solution Approach 114 4. Module Development 117 4.1 Economic Module – Module Development 117 4.1.1 General Approach 117 4.1.2 Calculation Scheme for Manual Operation 117 4.1.3 Calculation Scheme for Collaborative Robots 118 4.1.4 Calculation Scheme for Industrial Robots 120 4.2 Gripper Feasibility Module – Module Development 121 4.3 Rough Layout Discretization Module – Module Development 122 4.3.1 General Approach 122 4.3.2 Two-Dimensional Layout Pattern 123 4.3.3 Three-Dimensional Layout Pattern 125 4.4 Cycle Time Estimation Module – Module Development 126 4.4.1 General Approach 126 4.4.2 Reachability Study 127 4.4.3 Simulation Results 128 4.5 Collaborative Speed Estimation Module – Module Development 135 4.5.1 General Approach 135 4.5.2 Case 1: Quasi-static Contact with Hand 135 4.5.3 Case 2: Transient Contact with Hand 143 4.5.4 Case 3: Transient Contact with Shoulder 145 4.6 Synthesis – Module Development 149 5. Practical Verification 155 5.1 Use Case Overview 155 5.2 Gripper Feasibility 155 5.3 Layout Discretization 156 5.4 Collaborative Speed Estimation 157 5.5 Cycle Time Estimation 158 5.6 Economic Evaluation 160 5.7 Synthesis – Practical Verification 161 6. Results and Conclusions 165 6.1 Scientific Findings and Results 165 6.2 Critical Appraisal and Outlook 173Initially, industrial robots were mainly operated behind safety fences to account for the safety requirements. With production flexibilization, these sharp separation areas have been increasingly softened by utilizing external safety devices, such as distance sensors, to operate industrial robots fenceless. Based on this idea of coexistence or cooperation, safety technology has been integrated into the robot to enable true collaboration. These collaborative robots, or cobots, open up new application fields and fill the existing automation gap. But which automation variant is most suitable from an economic perspective? Present research dealt primarily isolated with one technology without comparing these systems regarding technological and economic specifics. Therefore, this doctoral thesis pursues a methodology to economically compare collaborative and industrial robots in fenceless machine tending systems. A particular focus lies on distilling the technical factors that mainly influence the profitability to receive a system understanding of the economic structure of both robot technology variants. For examination, the contents of such a planning scheme are described, categorized, systematized, and modularized. A suitable optimization model is presented on the economic side, while the feasibility regarding gripping, layout planning, robot velocities, and cycle time determination is assessed on the technical side. With deductive, simulative, empirical, and statistical methods, the system behavior of the single planning entities is analyzed to predict the overall profitability a priori with a minimum of investment,- production,- and cycle time information. It is demonstrated that the necessary planning data, in terms of layout composition, robot velocities, and cycle times, can be frontloaded to the project’s beginning with a reverse engineering approach. The net present value serves as the target figure, whose dependency on the human-robot interaction grade can be illustrated in an advantageousness diagram for the individual technical alternatives. Consequently, sound economic decisions can be made on a quantitative basis.:1. Introduction 25 1.1 Research Domain 25 1.2 Research Niche 26 1.3 Research Structure 28 2. State of the Art and Research 31 2.1 Turning Machines and Machine Tending 31 2.1.1 Tooling Machine Market Trends and Machine Tending Systems 31 2.1.2 Workpiece System 34 2.1.3 Machine System 36 2.1.4 Logistics System 39 2.1.5 Handling System 41 2.2 Robotics 43 2.2.1 Robot Installation Development and Application Fields 43 2.2.2 Fenceless Industrial and Collaborative Robots 48 2.2.3 Robot Grippers 55 2.3 Planning and Evaluation Methods 56 2.3.1 Planning of General and Manual Workstations 56 2.3.2 Cell Planning for Fully Automated and Hybrid Robot Systems 59 2.3.3 Robot Safety Planning 61 2.3.4 Economic Evaluation Methods 70 2.4 Synthesis - State of the Art and Research 71 3. Solution Approach 77 3.1 Need for Research and General Solution Approach 77 3.2 Use Case Delineation and Planning Focus 80 3.3 Economic Module – Solution Approach 86 3.4 Gripper Feasibility Module – Solution Approach 89 3.5 Rough Layout Discretization Model – Solution Approach 94 3.6 Cycle Time Estimation Module – Solution Approach 97 3.7 Collaborative Speed Estimation Module – Solution Approach 103 3.7.1 General Approach 103 3.7.2 Case 1: Quasi-static Contact with Hand 107 3.7.3 Case 2: Transient Contact with Hand 109 3.7.4 Case 3: Transient Contact with Shoulder 111 3.8 Synthesis – Solution Approach 114 4. Module Development 117 4.1 Economic Module – Module Development 117 4.1.1 General Approach 117 4.1.2 Calculation Scheme for Manual Operation 117 4.1.3 Calculation Scheme for Collaborative Robots 118 4.1.4 Calculation Scheme for Industrial Robots 120 4.2 Gripper Feasibility Module – Module Development 121 4.3 Rough Layout Discretization Module – Module Development 122 4.3.1 General Approach 122 4.3.2 Two-Dimensional Layout Pattern 123 4.3.3 Three-Dimensional Layout Pattern 125 4.4 Cycle Time Estimation Module – Module Development 126 4.4.1 General Approach 126 4.4.2 Reachability Study 127 4.4.3 Simulation Results 128 4.5 Collaborative Speed Estimation Module – Module Development 135 4.5.1 General Approach 135 4.5.2 Case 1: Quasi-static Contact with Hand 135 4.5.3 Case 2: Transient Contact with Hand 143 4.5.4 Case 3: Transient Contact with Shoulder 145 4.6 Synthesis – Module Development 149 5. Practical Verification 155 5.1 Use Case Overview 155 5.2 Gripper Feasibility 155 5.3 Layout Discretization 156 5.4 Collaborative Speed Estimation 157 5.5 Cycle Time Estimation 158 5.6 Economic Evaluation 160 5.7 Synthesis – Practical Verification 161 6. Results and Conclusions 165 6.1 Scientific Findings and Results 165 6.2 Critical Appraisal and Outlook 17

RUR53: an Unmanned Ground Vehicle for Navigation, Recognition and Manipulation

This paper proposes RUR53: an Unmanned Ground Vehicle able to autonomously navigate through, identify, and reach areas of interest; and there recognize, localize, and manipulate work tools to perform complex manipulation tasks. The proposed contribution includes a modular software architecture where each module solves specific sub-tasks and that can be easily enlarged to satisfy new requirements. Included indoor and outdoor tests demonstrate the capability of the proposed system to autonomously detect a target object (a panel) and precisely dock in front of it while avoiding obstacles. They show it can autonomously recognize and manipulate target work tools (i.e., wrenches and valve stems) to accomplish complex tasks (i.e., use a wrench to rotate a valve stem). A specific case study is described where the proposed modular architecture lets easy switch to a semi-teleoperated mode. The paper exhaustively describes description of both the hardware and software setup of RUR53, its performance when tests at the 2017 Mohamed Bin Zayed International Robotics Challenge, and the lessons we learned when participating at this competition, where we ranked third in the Gran Challenge in collaboration with the Czech Technical University in Prague, the University of Pennsylvania, and the University of Lincoln (UK).Comment: This article has been accepted for publication in Advanced Robotics, published by Taylor & Franci