Modular robots have the potential to revolutionize automation, as one can optimize their composition for any given task. However, finding optimal compositions is non-trivial. In addition, different compositions require different base positions and trajectories to fully use the potential of modular robots. We address this problem holistically for the first time by jointly optimizing the composition, base placement, and trajectory to minimize the cycle time of a given task. Our approach is evaluated on over 300 industrial benchmarks requiring point-to-point movements. Overall, we reduce cycle time by up to 25% and find feasible solutions in twice as many benchmarks compared to optimizing the module composition alone. In the first real-world validation of modular robots optimized for point-to-point movement, we find that the optimized robot is successfully deployed in nine out of ten cases in less than an hour.

Selecting an optimal robot, its base pose, and trajectory for a given task is currently mainly done by human expertise or trial and error. To evaluate automatic approaches to this combined optimization problem, we introduce a benchmark suite encompassing a unified format for robots, environments, and task descriptions. Our benchmark suite is especially useful for modular robots, where the multitude of robots that can be assembled creates a host of additional parameters to optimize. We include tasks such as machine tending and welding in synthetic environments and 3D scans of real-world machine shops. All benchmarks are accessible through cobra.cps.cit.tum.de, a platform to conveniently share, reference, and compare tasks, robot models, and solutions.

Industrial robots are essential for modern production but often struggle to adapt to new tasks. Modular (reconfigurable) robots can overcome this challenge by eliminating the need to replace the whole robot. However, finding the optimal assembly for a task remains difficult because a valid path has to be computed for each generated assembly – consuming a significant fraction of the computation time. Similar to online path planning, where previous approaches adapt known paths to a changing environment, we show that transferring paths from previously considered module assemblies accelerates path planning for the next assemblies. On average, our method reduces the planning time for single-goal tasks by 50%. The usefulness of our method is evaluated by integrating it in a genetic algorithm (GA) for optimizing assemblies and evaluating it on our benchmark suite CoBRA. Within the optimization loop for modular robots, the time used to check a single assembly is shortened by up to 50%.

Modular Reconfigurable Robots (MRRs) represent an exciting path forward for industrial robotics, opening up new possibilities for robot design. Compared to monolithic manipulators, they promise greater flexibility, improved maintainability, and cost-efficiency. However, there is no tool or standardized way to model and simulate assemblies of modules in the same way it has been done for robotic manipulators for decades. We introduce the Toolbox for Industrial Modular Robotics (Timor), a Python toolbox to bridge this gap and integrate modular robotics into existing simulation and optimization pipelines. Our open-source library offers model generation and task-based configuration optimization for MRRs. It can easily be integrated with existing simulation tools - not least by offering URDF export of arbitrary modular robot assemblies. Moreover, our experimental study demonstrates the effectiveness of Timor as a tool for designing modular robots optimized for specific use cases.

Humans and robots are increasingly sharing their workspaces to benefit from the precision, endurance, and strength of machines and the universal capabilities of humans. Instead of performing time-consuming real experiments, computer simulations of humans could help to optimally orchestrate human and robotic tasks—either for setting up new production cells or by optimizing the motion planning of already installed robots. Especially when human-robot coexistence is optimized using machine learning, being able to synthesize a huge number of human motions is indispensable. However, no solution exists that automatically creates a range of human motions from a high-level specification of tasks. We propose a novel method that automatically generates human motions from linear temporal logic specifications and demonstrate our approach by numerical examples.

In the past decade, the World Wide Web has been subject to dramatic changes. Web sites have evolved from static information resources to dynamic and interactive applications that are used for a broad scope of activities on a daily basis. To examine the consequences of these changes on user behavior, we conducted a long-term client-side Web usage study with twenty-five participants. This report presents results of this study and compares the user behavior with previous long-term browser usage studies, which range in age from seven to thirteen years. Based on the empirical data and the interview results, various implications for the interface design of browsers and Web sites are discussed. A major finding is the decreasing prominence of backtracking in Web navigation. This can largely be attributed to the increasing importance of dynamic, service-oriented Web sites. Users do not navigate on these sites searching for information, but rather interact with an online application to complete certain tasks. Furthermore, the usage of multiple windows and tabs has partly replaced back button usage, posing new challenges for user orientation and backtracking. We found that Web browsing is a rapid activity even for pages with substantial content, which calls for page designs that allow for cursory reading. Click maps provide additional information on how users interact with the Web on page level. Finally, substantial differences were observed between users, and characteristic usage patterns for different types of Web sites emphasize the need for more adaptive and customizable Web browsers.

This paper presents results of an extensive long-term click-stream study of Web browser usage. Focusing on character and challenges of page revisitation, previous findings from seven to thirteen years ago are updated. The term page re-visit had to be differentiated, since the recurrence rate--the key measure for the share of page revisits--turns out to strongly depend on interpretation. We identify different types of revisitation that allow assessing the quality of current user support and developing concepts for new tools.

This paper presents results of a long-term client-side Web usage study, updating previous studies that range in age from five to ten years. We focus on three aspects of Web navigation: changes in the distribution of navigation actions, speed of navigation and within-page navigation. “Navigation actions��? corresponding to users’ individual page requests are discussed by type. We reconfirm links to be the most important navigation element, while backtracking has lost more than half of its previously reported share and form submission has become far more common. Changes of the Web and the browser interfaces are candidates for causing these changes. Analyzing the time users stayed on pages, we confirm Web navigation to be a rapidly interactive activity. A breakdown of page characteristics shows that users often do not take the time to read the available text or consider all links. The performance of the Web is analyzed and reassessed against the resulting requirements. Finally, habits of within-page navigation are presented. Although most selected hyperlinks are located in the top left corner of the screen, in nearly a quarter of all cases people choose links that require scrolling. We analyzed the available browser real estate to gain insights for the design of non-scrolling Web pages.

The CVP Cyberspace Visualization Project addresses interactive overview visualizations of Web spaces for enhancing orientation, navigation and communication when browsing or searching the WWW. This paper presents a collection of requirements which such visualizations should fulfil. An algorithm is described generating recognizable, hierarchically structured views of interconnected Web objects. The CVP is outlined as improving current tools for Web navigation and communication. It combines 3D overviews with the mutual representation of users, providing first steps towards the Web browsers of the next generation.