Housekeeping with multiple autonomous robots: representation, reasoning, and execution

We consider a housekeeping domain with static or movable objects, where the goal is for multiple autonomous robots to tidy a house collaboratively in a given amount of time. This domain is challenging in the following ways: commonsense knowledge (e.g., expected locations of objects in the house) is required for intelligent behavior of robots; geometric constraints are required to find feasible plans (e.g., to avoid collisions); in case of plan failure while execution (e.g., due to a collision with movable objects whose presence and location are not known in advance or due to heavy objects that cannot be lifted by a single robot), recovery is required depending on the cause of failure; and collaboration of robots is required to complete some tasks (e.g., carrying heavy objects). We introduce a formal planning, execution and monitoring framework to address the challenges of this domain, by embedding knowledge representation and automated reasoning in each level of decision-making (that consists of discrete task planning, continuous motion planning, and plan execution), in such a way as to tightly integrate these levels. At the high-level, we represent not only actions and change but also commonsense knowledge in a logicbased formalism. Geometric reasoning is lifted to the high-level by embedding motion planning in the domain description. Then a discrete plan is computed for each robot using an automated reasoner. At the mid-level, if a continuous trajectory cannot be computed by a motion planner because the discrete plan is not feasible at the continuous-level, then a different plan is computed by the automated reasoner subject to some (temporal) conditions represented as formulas. At the low-level, if the plan execution fails, then a new continuous trajectory is computed by a motion planner at the mid-level or a new discrete plan is computed using an automated reasoner at the high-level. We illustrate the applicability of this formal framework with a simulation of a housekeeping domain

Digital Disruption in Teaching and Testing

This book provides a significant contribution to the increasing conversation concerning the place of big data in education. Offering a multidisciplinary approach with a diversity of perspectives from international scholars and industry experts, chapter authors engage in both research- and industry-informed discussions and analyses on the place of big data in education, particularly as it pertains to large-scale and ongoing assessment practices moving into the digital space. This volume offers an innovative, practical, and international view of the future of current opportunities and challenges in education and the place of assessment in this context

Industrial Robot Collision Handling in Harsh Environments

The focus in this thesis is on robot collision handling systems, mainly collision detection and collision avoidance for industrial robots operating in harsh environments (e.g. potentially explosive atmospheres found in the oil and gas sector). Collision detection should prevent the robot from colliding and therefore avoid a potential accident. Collision avoidance builds on the concept of collision detection and aims at enabling the robot to find a collision free path circumventing the obstacle and leading to the goal position. The work has been done in collaboration with ABB Process Automation Division with focus on applications in oil and gas. One of the challenges in this work has been to contribute to safer use of industrial robots in potentially explosive environments. One of the main ideas is that a robot should be able to work together with a human as a robotic co-worker on for instance an oil rig. The robot should then perform heavy lifting and precision tasks, while the operator controls the steps of the operation through typically a hand-held interface. In such situations, when the human works alongside with the robot in potentially explosive environments, it is important that the robot has a way of handling collisions. The work in this thesis presents solutions for collision detection in paper A, B and C, thereafter solutions for collision avoidance are presented in paper D and E. Paper A approaches the problem of collision avoidance comparing an expert system and a hidden markov model (HMM) approach. An industrial robot equipped with a laser scanner is used to gather environment data on arbitrary set of points in the work cell. The two methods are used to detect obstacles within the work cell and shows a different set of strengths. The expert system shows an advantage in algorithm performance and the HMM method shows its strength in its ease of learning models of the environment. Paper B builds upon Paper A by incorporating a CAD model of the environment. The CAD model allows for a very fast setup of the expert system where no manual map creation is needed. The HMM can be trained based on the CAD model, which addresses the previous dependency on real sensor data for training purposes. Paper C compares two different world-model representation techniques, namely octrees and point clouds using both a graphics processing unit (GPU) and a central processing unit (CPU). The GPU showed its strength for uncompressed point clouds and high resolution point cloud models. However, if the resolution gets low enough, the CPU starts to outperform the GPU. This shows that parallel problems containing large data sets are suitable for GPU processing, but smaller parallel problems are still handled better by the CPU. In paper D, real-time collision avoidance is studied for a lightweight industrial robot using a development platform controller. A Microsoft Kinect sensor is used for capturing 3D depth data of the environment. The environment data is used together with an artificial potential fields method for generating virtual forces used for obstacle avoidance. The forces are projected onto the end-effector, preventing collision with the environment while moving towards the goal. Forces are also projected on to the elbow of the 7-Degree of freedom robot, which allows for nullspace movement. The algorithms for manipulating the sensor data and calculating virtual forces were developed for the GPU, this resulted in fast algorithms and is the enabling factor for real-time collision avoidance. Finally, paper E builds on the work in paper D by providing a framework for using the algorithms on a standard industrial controller and robot with minimal modifications. Further, algorithms were specifically developed for the robot controller to handle reactive movement. In addition, a full collision avoidance system for an end-user application which is very simple to implement is presented. The work described in this thesis presents solutions for collision detection and collision avoidance for safer use of robots. The work is also a step towards making businesses more competitive by enabling easy integration of collision handling for industrial robots

The Realities and Futures of Work

What do we know about the current realities of work and its likely futures? What choices must we make and how will they affect those futures? Many books about the future of work start by talking about the latest technology, and focus on how technology is going to change the way we work. And there is no doubt that technology will have huge impacts. However, to really understand the direction in which work is going, and the impact that technology and other forces will have, we need to first understand where we are. This book covers topics ranging from the ‘mega-drivers of change’ at work, power, globalisation and financialisation, to management, workers, digitalisation, the gig economy, gender, climate change, regulation and deregulation. In doing this, it refers to some of the great works of science fiction. It demolishes several myths, such as that the employment relationship is doomed, that we are all heading to becoming ‘freelancers’ or ‘gig workers’ one day, that most jobs will be destroyed by technological change, that the growth in jobs will mainly be in STEM fields, that we will no longer value collectivism as we will all be ‘individuals’, or that the death of unionism is inevitable. The Realities and Futures of Work also rejects the idea of technological determinism—that whatever will be, will be, thanks to technological change—and so it refuses to accept that we simply need to prepare to adapt ourselves to the future by judicious training since there is nothing else we can do about it. Instead, this book provides a realistic basis for thinking about both the present and the future. It emphasises the choices we make, and the implications of those choices for the future of work

Advancing accountability for human rights violations through citizen media - an African perspective

Thesis (LLD)--University of Pretoria, 2022.In the year 2020, there were two key events that captured global attention and further reinforced the power of citizen media evidence in exposing the truth and advancing justice. The first was the killing of George Floyd by a police officer in the United States of America that was filmed by witnesses and disseminated via social media, while the second was the Lekki Toll Gate shooting carried out by Nigerian security forces against unarmed protesters in Lagos, Nigeria which was livestreamed on Instagram. The citizen videos from these two incidents sparked global outrage, triggered investigations and, in the George Floyd case, led to court convictions. However, these examples of citizen media evidence exposing atrocities are not isolated cases, neither are they new. The ubiquity of cellphone cameras combined with the popular adoption of social media networks have radically transformed the sphere of human rights in an unprecedented way, resulting in more people documenting and exposing human rights abuses. This proliferation of citizen media evidence has enabled victims of atrocities to obtain remedy and hold the powerful to account. At the same time, leveraging citizen media evidence to achieve justice is persistently being hindered by significant legal, social, political, technological and institutional barriers. This thesis is therefore an attempt to interrogate these barriers impeding the widespread use of citizen media evidence before domestic and international judicial mechanisms. This thesis engaged in an analysis of select African judicial systems, while also drawing lessons from international courts and tribunals as well as other domestic courts around the world. A socio-legal approach was adopted, through which the research was able to identify and isolate complex societal challenges and the role law can play in transforming the situation for the better. A key finding of this research is that in a number of African countries, the law of evidence is not sufficiently robust to meet the challenges of the digital era. I therefore proposed a model law on citizen media evidence as one of the ways to ensure that evidence of human rights violations can continue to be used in ways that protect the vulnerable, deliver justice for victims, and prosecute perpetrators and offenders. The analysis of African case law and statutory provisions that underpinned sections of this thesis constitute original contribution to a field of research that rarely centers experiences from the Global South, especially those on the African continent.German Academic Exchange Service (Deutscher Akademischer Austauschdienst - DAAD)Centre for Human RightsLLDUnrestricte