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Modern Operating Systems

Industrial robots, automated manufacturing, and efficient logistics processes are at the heart of the upcoming fourth industrial revolution. While there are seminal studies on the vulnerabilities of cyber-physical systems in the industry, as of today there has been no systematic analysis of the security of industrial robot controllers. We examine the standard architecture of an industrial robot and analyze a concrete deployment from a systems security standpoint. Then, we propose an attacker model and confront it with the minimal set of requirements that industrial robots should honor: precision in sensing the environment, correctness in execution of control logic, and safety for human operators. Following an experimental and practical approach, we then show how our modeled attacker can subvert such requirements through the exploitation of software vulnerabilities, leading to severe consequences that are unique to the robotics domain. We conclude by discussing safety standards and security challenges in industrial robotics.

/pdf/an-experimental-security-analysis-of-an-industrial-robot-17avaqe9qh.pdf

An Experimental Security Analysis of an Industrial Robot Controller

A Comprehensive Survey of Recent Trends in Cloud Robotics Architectures and Applications

Detection of Cyber-attacks to indoor real time localization systems for autonomous robots

Increases in the prevalence of dementia and Alzheimer’s disease (AD) are a growing challenge in many nations where healthcare infrastructures are ill-prepared for the upcoming demand for personal caregiving. To help individuals with AD live at home for longer, we are developing a mobile robot, called ED, intended to assist with activities of daily living through visual monitoring and verbal prompts in cases of difficulty. In a series of experiments, we study speech-based interactions between ED and each of 10 older adults with AD as the latter complete daily tasks in a simulated home environment. Traditional automatic speech recognition is evaluated in this environment, along with rates of verbal behaviors that indicate confusion or trouble with the conversation. Analysis reveals that speech recognition remains a challenge in this setup, especially during household tasks with individuals with AD. Across the verbal behaviors that indicate confusion, older adults with AD are very likely to simply ignore the robot, which accounts for over 40p of all such behaviors when interacting with the robot. This work provides a baseline assessment of the types of technical and communicative challenges that will need to be overcome for robots to be used effectively in the home for speech-based assistance with daily living.

/pdf/speech-interaction-with-personal-assistive-robots-supporting-ccekoo56dk.pdf

Speech Interaction with Personal Assistive Robots Supporting Aging at Home for Individuals with Alzheimer’s Disease

With the expected introduction of robots into our daily lives, providing mechanisms to avoid undesired attacks and exploits in robot communication software is becoming increasingly required. Just as during the beginnings of the computer age (Pfleeger and Pfleeger, 2002), robotics is established in a “happy naivety,” where security rules against external attacks are not adopted, assuming that robotics knowledgeable people are well intended. While this may have been true in the past, the mass adoption of robots will increase the possibilities of attacks. This fact is especially relevant in defense, medical and other critical fields involving humans, where tampering can result in serious bodily harm and/or privacy invasions. For these reasons, we consider that researchers and industry should deploy efforts in cyber safety and acquire good practices when developing and distributing robot software. We propose the term Cryptobotics as a unifying term for research and applications of computer and microcontrollers’ security measures in robotics.

/pdf/cryptobotics-why-robots-need-cyber-safety-2mv3arp8cb.pdf

Cryptobotics: Why Robots Need Cyber Safety

Programming by demonstration (PbD) allows matching the kinematic movements of a robot with those of a human. The presented Continuous Goal-Directed Actions (CGDA) is able to additionally encode the effects of a de- monstrated action, which are not encoded in PbD. CGDA allows generalization, recognition and execution of action ef- fects on the environment. In addition to analyzing kinematic parameters (joint positions/velocities, etc.), CGDA focuses on changes produced on the object due to an action (spatial, color, shape, etc.). By tracking object features during action execution, we create a trajectory in an n-dimensional feature space that represents object temporal states. Discretized action repetitions provide us with a cloud of points. Action gener- alization is accomplished by extracting the average point of each sequential temporal interval of the point cloud. These points are interpolated using Radial Basis Functions, obtaining a generalized multidimensional object feature trajectory. Action recognition is performed by comparing the trajectory of a query sample with the generalizations. The trajectories discrepancy score is obtained by using Dynamic Time Warping (DTW). Robot joint trajectories for execution are computed in a simulator through evolutionary computation. Object features are extracted from sensors, and each evolutionary individual fitness is measured using DTW, comparing the simulated action with the generalization.

/pdf/action-effect-generalization-recognition-and-execution-3aejyw9zqs.pdf

Action effect generalization, recognition and execution through Continuous Goal-Directed Actions

Humanoids can learn motor skills through the programming by demonstration framework, which allows matching the kinematic movements of a robot with those of a human. Continuous goal-directed actions (CGDA) is a framework that can complement the paradigm of robot imitation. Instead of kinematic parameters, its encoding is centered on the changes an action produces on object features. The features can be any measurable characteristic of the object such as color, area, etc. The execution of actions encoded as CGDA allows a robot-configuration independent achievement of tasks, avoiding the correspondence problem. By tracking object features during action execution, we create a trajectory in an n-dimensional feature space that represents object temporal states, allowing generalization, recognition, and execution of action effects on the environment. Experiments have been performed, using a humanoid robot in a simulated environment. Evolutionary computation was used for joint parameter calculation of a humanoid ...

Humanoid robot imitation through continuous goal-directed actions: an evolutionary approach

We present Robot Devastation, a multiplayer augmented reality game using low-cost robots. Players can assemble their low-cost robotic platforms and connect them to the central server, commanding them through their home PCs. Several low-cost platforms were developed and tested inside the game.

/pdf/robot-devastation-using-diy-low-cost-platforms-for-35xd62cec8.pdf

Robot devastation: Using DIY low-cost platforms for multiplayer interaction in an augmented reality game

In this paper, we study how human-robot interaction can be beneficial on the Continuous Goal-Directed Actions (CGDA) framework. Specifically, a system for robot discovery of motor primitives from random human-guided movements has been developed. These guided motor primitives (GMP) are used as scaffolds to reproduce a goal-directed actions. CGDA encodes goals as the changes produced on object features (color, area, etc) due to actions. This paper focuses on using motor primitives extracted from human-guided random robot movements to execute these goal-directed actions. The human guides the robot joints in random movements, which are later divided in small segments. These segments are compared in terms of joint positions and selected to be diverse. To perform goal-directed actions, the robot must discover an adequate sequence of GMP. To discover these sequences we organize the primitives as a tree with incremental depths (where each node represents a primitive) and use a breadth-first search. In one of the experiments performed, the robot executes a task based on spatial object features. In the other experiment, the goal is to paint a wall by following a color feature trajectory.

http://roboticslab.uc3m.es/roboticslab/sites/default/files/morante2014on-preprint.pdf

Santiago Morante

Papers

Cryptobotics: Why Robots Need Cyber Safety

Action effect generalization, recognition and execution through Continuous Goal-Directed Actions

Humanoid robot imitation through continuous goal-directed actions: an evolutionary approach

Robot devastation: Using DIY low-cost platforms for multiplayer interaction in an augmented reality game

On using guided motor primitives to execute Continuous Goal-Directed Actions