Nut Unfastening by Robotic Surface Exploration

In this paper, we present a novel concept and primary investigations regarding automated unfastening of hexagonal nuts by means of surface exploration with a compliant robot. In contrast to the conventional industrial approaches that rely on custom-designed motorised tools and mechanical tool changers, we propose to use robot fingers to position, grasp and unfasten unknown random-sized hexagonal nuts, which are arbitrarily positioned in the robot’s task space. Inspired by how visually impaired people handle unknown objects, in this work, we use information observed from surface exploration to devise the unfastening strategy. It combines torque monitoring with active compliance for the robot fingers to smoothly explore the object’s surface. We implement a shape estimation technique combining scaled iterative closest point and hypotrochoid approximation to estimate the location as well as contour profile of the hexagonal nut so as to accurately position the gripper fingers. We demonstrate this work in the context of dismantling an electrically driven vehicle battery pack. The experiments are conducted using a seven degrees of freedom (DoF)–compliant robot fitted with a two-finger gripper to unfasten four different sized randomly positioned hexagonal nuts. The obtained results suggest an overall exploration and unfastening success rate of 95% over an average of ten trials for each nut.

Evaluation of Kinematic and Compliance Calibration of Serial Articulated Industrial Manipulators

As long as industrial robots are programmed by teach programming, their positioning accuracy is unimportant. With a wider implementation of offline programming and new applications such as machining, ensuring a higher positioning accuracy of industrial robots over the entire working space has become very important. In this paper, we first review the measurement schemes of end effector poses. We then outline kinematic models of serial articulated industrial manipulators to quantify the positioning accuracy with a focus on the extension of the classical Denavit-Hartenberg (DH) models to include rotary axis error motions. Subsequently, we expand the discussion on kinematic models to compliant robot models. The review highlights compliance models that are applied to calculate the elastic deformation produced by forces, namely gravity and external loads. Model-based numerical compensation plays an important role in machine tool control. This paper aims to present state-of-the-art technical issues and future research directions for the implementation of model-based numerical compensation schemes for industrial robots.

From Learning to Relearning: A Framework for Diminishing Bias in Social Robot Navigation

The exponentially increasing advances in robotics and machine learning are facilitating the transition of robots from being confined to controlled industrial spaces to performing novel everyday tasks in domestic and urban environments. In order to make the presence of robots safe as well as comfortable for humans, and to facilitate their acceptance in public environments, they are often equipped with social abilities for navigation and interaction. Socially compliant robot navigation is increasingly being learned from human observations or demonstrations. We argue that these techniques that typically aim to mimic human behavior do not guarantee fair behavior. As a consequence, social navigation models can replicate, promote, and amplify societal unfairness, such as discrimination and segregation. In this work, we investigate a framework for diminishing bias in social robot navigation models so that robots are equipped with the capability to plan as well as adapt their paths based on both physical and social demands. Our proposed framework consists of two components: learning which incorporates social context into the learning process to account for safety and comfort, and relearning to detect and correct potentially harmful outcomes before the onset. We provide both technological and societal analysis using three diverse case studies in different social scenarios of interaction. Moreover, we present ethical implications of deploying robots in social environments and propose potential solutions. Through this study, we highlight the importance and advocate for fairness in human-robot interactions in order to promote more equitable social relationships, roles, and dynamics and consequently positively influence our society.

A Cryptography-Powered Infrastructure to Ensure the Integrity of Robot Workflows

With the growing popularity of robots, the development of robot applications is subject to an ever increasing number of additional requirements from e.g., safety, legal and ethical sides. The certification of an application for compliance to such requirements is an essential step in the development of a robot program. However, at this point in time it must be ensured that the integrity of this program is preserved meaning that no intentional or unintentional modifications happen to the program until the robot executes it. Based on the abstraction of robot programs as workflows we present in this work a cryptography-powered distributed infrastructure for the preservation of robot workflows. A client composes a robot program and once it is accepted a separate entity provides a digital signature for the workflow and its parameters which can be verified by the robot before executing it. We demonstrate a real-world implementation of this infrastructure using a mobile manipulator and its software stack. We also provide an outlook on the integration of this work into our larger undertaking to provide a distributed ledger-based compliant robot application development environment.

A Gesture-Based Teleoperation System for Compliant Robot Motion

Currently, the gesture-based teleoperation system cannot generate precise and compliant robot motions because human motions have the characteristics of uncertainty and low-resolution. In this paper, a novel, gesture-based teleoperation system for compliant robot motion is proposed. By using the left hand as the commander and the right hand as a positioner, different operation modes and scaling ratios can be tuned on-the-fly to meet the accuracy and efficiency requirements. Moreover, a vibration-based force feedback system was developed to provide the operator with a telepresence capability. The pick-and-place and peg-in-hole tasks were used to test the effectiveness of the teleoperation system we developed. The experiment results prove that the gesture-based teleoperation system is effective at handling compliant robot motions.