Jeremy A. Marvel

Performance Metrics of Speed and Separation Monitoring in Shared Workspaces

A set of metrics is proposed that evaluates speed and separation monitoring efficacy in industrial robot environments in terms of the quantification of safety and the effects on productivity. The collision potential is represented by separation metrics and sensor uncertainty based on perceived noise and bounding region radii. In the event of a bounding region collision between a robot and an obstacle during algorithm evaluation, the severity of the separation failure is reported as a percentage of volume penetration.

Characterizing Task-Based Human–Robot Collaboration Safety in Manufacturing

A new methodology for describing the safety of human-robot collaborations is presented. Taking a task-based perspective, a risk assessment of a collaborative robot system safety can be evaluated offline during the initial design stages. This risk assessment factors in such elements as tooling, the nature and duration of expected contacts, and any amortized transfer of pressures and forces onto a human operator. Risk assessments of example tasks are provided for illustrative purposes.

Technology readiness levels for randomized bin picking

A proposal for the utilization of Technology Readiness Levels to the application of unstructured bin picking is discussed. A special session was held during the 2012 Performance Metrics for Intelligent Systems workshop to discuss the challenges and opportunities associated with the bin picking problem, and to identify the potentials for applying an industry-wide standardized assessment and reporting framework such as Technology Readiness Levels to bin picking. Representative experts from government, academia, and industry were assembled to form a special panel to share their insights into the challenge.

Development of Standard Test Methods for Unmanned and Manned Industrial Vehicles Used Near Humans

The National Institute of Standards and Technology (NIST) has been researching human-robot-vehicle collaborative environments for automated guided vehicles (AGVs) and manned forklifts. Safety of AGVs and manned vehicles with automated functions (e.g., forklifts that slow/stop automatically in hazardous situations) are the focus of the American National Standards Institute/Industrial Truck Safety Development Foundation (ANSI/ITSDF) B56.5 safety standard. Recently, the NIST Mobile Autonomous Vehicle Obstacle Detection/Avoidance (MAVODA) Project began researching test methods to detect humans or other obstacles entering the vehicle’s path. This causes potential safety hazards in manufacturing facilities where both line-of-sight and non-line-of-sight conditions are prevalent. The test methods described in this paper address both of these conditions. These methods will provide the B56.5 committee with the measurement science basis for sensing systems - both non-contact and contact - that may be used in manufacturing facilities.

A Cross-Domain Survey of Metrics for Modelling and Evaluating Collisions

This paper provides a brief survey of the metrics for measuring probability, degree, and severity of collisions as applied to autonomous and intelligent systems. Though not exhaustive, this survey evaluates the state-of-the-art of collision metrics, and assesses which are likely to aid in the establishment and support of autonomous system collision modelling. The survey includes metrics for 1) robot arms; 2) mobile robot platforms; 3) nonholonomic physical systems such as ground vehicles, aircraft, and naval vessels, and; 4) virtual and mathematical models.

Multi-Robot Assembly Strategies and Metrics

We present a survey of multi-robot assembly applications and methods and describe trends and general insights into the multi-robot assembly problem for industrial applications. We focus on fixtureless assembly strategies featuring two or more robotic systems. Such robotic systems include industrial robot arms, dexterous robotic hands, and autonomous mobile platforms, such as automated guided vehicles. In this survey, we identify the types of assemblies that are enabled by utilizing multiple robots, the algorithms that synchronize the motions of the robots to complete the assembly operations, and the metrics used to assess the quality and performance of the assemblies.

Integrating occlusion monitoring into human tracking for robot speed and separation monitoring

Collaborative robots are used in close proximity to humans to perform a variety of tasks, while more traditional industrial robots are required to be stopped whenever a human enters their work-volumes. Instead of relying on physical barriers or merely detecting when someone enters the area, the collaborative system must monitor the position of every person who enters the work space in time for the robot to react. The TC 184/SC 2/WG 3 Industrial Safety group within the International Organization for Standard(ISO) is developing the standards to help ensure collaborative robots operate safely. Collaborative robots require sophisticated sensing technologies that must handle dynamic interactions between the robot and the human. One potential safety risk is the occlusion of a safety sensors field of view due to placement of objects or the movement of people in front of a safety sensor. In this situation the robot could shut down as soon as even a single sensor was partially occluded. Unfortunately this could greatly diminish the extent to which the robot could work collaboratively. In this paper we examine how a human tracking system using multiple laser line scanners [3]was adapted to work with a robot Speed and Separation Monitoring (SSM) safety system and further modified to include occlusion monitoring.

Performance evaluation of consumer-grade 3D sensors for static 6DOF pose estimation systems

Low-cost 3D depth and range sensors are steadily becoming more widely available and affordable, and thus popular for robotics enthusiasts. As basic research tools, however, their accuracy and performance are relatively unknown. In this paper, we describe a framework for performance evaluation and measurement error analysis for 6 degrees of freedom pose estimation systems using traceable ground truth instruments. Characterizing sensor drift and variance, and quantifying range, spatial and angular accuracy, our framework focuses on artifact surface fitting and static pose analysis, reporting testing and environmental conditions in compliance with the upcoming ASTM E57.02 standard.

Automated Planning for Robotic Cleaning Using Multiple Setups and Oscillatory Tool Motions

This paper presents planning algorithms for robotic cleaning of stains on nonplanar surfaces. Access to different portions of the stain may require frequent repositioning and reorienting of the object. Some portions with prominent stain may require multiple passes to remove the stain completely. Two robotic arms have been used in the experiments. The object is immobilized with one arm and the cleaning tool is manipulated with the other. The algorithm generates a sequence of reorientation and repositioning moves required to clean the part after analyzing the stain. The plan is generated by accounting for the kinematic constraints of the robot. Our algorithm uses a depth-first branch-and-bound search to generate setup plans. Cleaning trajectories are generated and optimal cleaning parameters are selected by the algorithm. We have validated our approach through numerical simulations and robotic cleaning experiments with two KUKA robots.Note to Practitioners—We encounter nonrepetitive cleaning tasks everyday in both industrial and household environments. Variations in stain pattern, geometry, and material of the object make it difficult to manually program robots for such tasks. In this paper, we present planning algorithms to automate the cleaning task using robots. The practical impact of our approach is evidenced by the actual robot results involving realistic examples like cleaning of hard paint stains on curved surfaces and rust on metal surfaces. Practitioners from industry can use the methods presented in this paper to develop automated robotic systems for nonrepetitive tasks like cleaning and polishing. Our approach caters to the primary requirements of these applications like multiple setups, multiple passes within each setup, and determination of optimal motion parameters like velocity, force, and oscillation frequency of the cleaning tool.

Simplified framework for robot coordinate registration for manufacturing applications

A simplified framework is introduced for automatically and quickly registering the Cartesian coordinate systems of industrial robots to any other arbitrary coordinate system. This framework includes both explicit and implicit (sensor-based) registration techniques using as few as three reference poses per robot, and presents different methods for measuring registration uncertainty. Driven by the guiding principles of simplifying the registration process to enable rapid installation by non-expert users, a mathematical basis for fast system registration is presented. We also present methods for quickly and inexpensively approximating the registration errors, and outline mechanisms for improving registration performance. Several case study examples are provided in which the registration performance is captured across four different registration methods, and two different robots. A reference motion capture system is used to capture post-registration positioning accuracy of the robots, a sampling-based registration estimation technique is assessed, and results are systematically quantified.