Collision Detection and Reaction: A Contribution to Safe Physical Human-Robot Interaction

In the framework of physical Human-Robot Interaction (pHRI), methodologies and experimental tests are presented for the problem of detecting and reacting to collisions between a robot manipulator and a human being. Using a lightweight robot that was especially designed for interactive and cooperative tasks, we show how reactive control strategies can significantly contribute to ensuring safety to the human during physical interaction. Several collision tests were carried out, illustrating the feasibility and effectiveness of the proposed approach. While a subjective “safety” feeling is experienced by users when being able to naturally stop the robot in autonomous motion, a quantitative analysis of different reaction strategies was lacking. In order to compare these strategies on an objective basis, a mechanical verification platform has been built. The proposed collision detection and reactions methods prove to work very reliably and are effective in reducing contact forces far below any level which is dangerous to humans. Evaluations of impacts between robot and human arm or chest up to a maximum robot velocity of 2.7 m/s are presented

The driver concept for the DLR Lightweight Robot III

In this paper we present the synchronization and driver architecture of the DLR LWR-III, which supplies an easy to use interface for applications. For our purpose we abstracted the robot hardware entirely from the control algorithms using the common device driver concept of modern operating systems. The software architecture is split into two modular parts. On the one side, there are device drivers that communicate with the hardware components. On the other side, there are realtime ap- plications realized as Simulink Models, which provide advanced control algorithms. This ensures a clean separation between the two modules and provides a communication over a common and approved interface. Furthermore we investigated how we can ensure synchronization to the hardware over the device driver interfaces and how we can ensure that it meets hard realtime requirements. The main result of this paper is to realize a synchronization between LWR-III hardware and Simulink control applications while targeting small latencies with respect to hard realtime requirements. The design is implemented and verified on WindRiverTM VxWorksTM

Master of Science

thesisFilter Bank Multicarrier (FB-MC) is a technique similar to Orthogonal Frequency Division Multiplexing (OFDM), used to divide the spectrum of a transceiver into multiple subcarriers or channels. When a single symbol is repeated across all subcarriers, its energy is spread across the entire spectrum. This is referred to as Filter Bank Multicarrier Spread Spectrum (FB-MC-SS). The design of a preamble or training sequence used in the packet construction of a FB-MC-SS transceiver system is explored in this thesis. The preamble is used to acquire an estimate of the channel impulse response and noise variance for each subcarrier. This information is then used to undo the effect of the channel and perform Maximum Ratio Combining (MRC) across all subcarriers. An alternating {+1, âˆ'1} sequence has been previously proposed for its implementation simplicity. An alternating {+1,âˆ'1} sequence leads to detection advantages as a result of the impulse response of the matched filter. An alternating {+1,âˆ'1} sequence also presents many disadvantages. Mainly, the sequence is susceptible to interference because of its distinct frequency. The alternating {+1, âˆ'1} sequence also has a higher probability of detection by unauthorized users. To combat these deficiencies of the alternating {+1,âˆ'1} sequence, pseudorandom sequences are explored in this thesis. The goal of the pseudorandom sequence is to gain ro- bustness without forfeiting the packet’s detectability by intended receivers. Pseudorandom Polyphase and Maximum Length Binary sequences are explored as randomized preambles. Both the alternating {+1, âˆ'1} sequence and the pseudorandom sequence are implemented separately in the FB-MC-SS transceiver on a Xilinx FPGA to compare resource utilizations. Pseudorandom Polyphase preamble sequences lead to robust channel frequency response and noise variance estimation in interfered environments. Although alternating {+1, âˆ'1} sequence leads to straightforward packet detection and simple FPGA implementation, the susceptibility of an alternating {+1, âˆ'1} preamble to interference makes a pseudorandom preamble sequence more desirable

A Hierarchical Human-Robot Interaction-Planning Framework for Task Allocation in Collaborative Industrial Assembly Processes

In this paper we propose a framework for task allocation in human-robot collaborative assembly planning. Our framework distinguishes between two main layers of abstraction and allocation. In the higher layer we use an abstract world model, incorporating a multi-agent human-robot team approach in order to describe the collaborative assembly planning problem. From this, nominal coordinated skill sequences for every agent are produced. In order to be able to treat humans and robots as agents of the same form, we move relevant differences/peculiarities into distinct cost functions. The layer beneath handles the concrete skill execution. On atomic level, skills are composed of complex hierarchical and concurrent hybrid state machines, which in turn coordinate the real-time behavior of the robot. Their careful design allows to cope with unpredictable events also on decisional level without having to explicitly plan for them, instead one may rely also on manually designed skills. Such events are likely to happen in dynamic and potentially partially known environments, which is especially true in case of human presence. © 2017 IEEEEU/H2020/688857/E

A Comparison of Braking Strategies for Elastic Joint Robots

It has recently been shown that intrinsically elastic robots are capable of outperforming rigid robots in terms of peak velocity by making systematic use of energy storage and release. Certainly, high link side velocities are beneficial for performance, however, they also increase the probability of self damage or human injury in case of a collision. To ensure the physical integrity of both human and robot, it is therefore crucial to avoid potentially dangerous collisions and react in a compliant manner if unwanted contact has occurred or may occur unforeseeable. In this paper, we consider the most intuitive collision anticipation and pre-reaction scheme, namely stopping an elastic robot, if possible in minimum time. For 1-DOF elastic joints with limited elastic deflection we extend existing model-based and model-free controllers and compare their performance. Furthermore, we analyze the braking trajectory that is achieved with the different strategies. The 1-DOF solution is extended to the double pendulum case, where we show that feasible estimates for maximum and final position can be obtained at the very first instant of braking

Human Like Adaptation of Force and Impedance in Stable and Unstable Tasks

Abstract—This paper presents a novel human-like learning con-troller to interact with unknown environments. Strictly derived from the minimization of instability, motion error, and effort, the controller compensates for the disturbance in the environment in interaction tasks by adapting feedforward force and impedance. In contrast with conventional learning controllers, the new controller can deal with unstable situations that are typical of tool use and gradually acquire a desired stability margin. Simulations show that this controller is a good model of human motor adaptation. Robotic implementations further demonstrate its capabilities to optimally adapt interaction with dynamic environments and humans in joint torque controlled robots and variable impedance actuators, with-out requiring interaction force sensing. Index Terms—Feedforward force, human motor control, impedance, robotic control. I

Electronic Library of Medicine - Jordan: Experience in the Digital Transformation and Managing COVID-19 Crisis

During COVID-19 pandemic Electronic Library of Medicine – Jordan (ELM) was on the upfront of dealing with the crisis. ELM worked on a response plan for the Digital Transformation of its online services with focus on COVID-19. The plan strategy consisted of four phases: preparation, implementation, evaluation and sustainability. The immediate management for COVID-19 pandemic was done through having a dedicated COVID-19 Knowledge Center and digitizing all training and educational sessions. An online survey for the evaluation of the impact on the Digital Transformation of library services was done. Evaluation results showed satisfactory impact. The COVID-19 pandemic was an opportunity to ELM, and it even enhanced the library services and training. Challenges concerning sustainability and accreditation of the continuing professional development need to be addressed with concerned authoritative parties within Jordan