The research at hand is part of the autonomous excavator project Thor. The long term-goal is the development of an excavator which is capable of performing landscaping tasks without human intervention. As this machine creates huge forces, safety plays an important role. This research extends the behavior-based trajectory generation for the excavation and truck loading operation, working for the undisturbed case only, with collision avoidance concerning obstacles and the machine itself. Based on a data efficient cylinder-coordinate octree for storing obstacles, joint movements are inhibited or actively influenced to prevent the machine from hitting objects and itself. Additionally, this research shows the suitability of the extensible reactive behavior-based control approach for the automation of construction machines.

The Climbing Robot CREA is developed to climb up flat concrete walls. Due to its big size and weight the robot uses the suction system to generate necessary adhesive force. This suction system consists of eleven chambers which are thermodynamically connected to one common reservoir. The robot also uses the wheel-based locomotion which introduces chalenging control dilema when integrating with suction system. This paper addresses these difficulties by introducing new control scheme that is able to reach a satisfactory trade-off between contradictory criteria. An exponentially stable controller is developed for each chamber that engages automatically with wall and generates desired adhesive force with lowest possible friction and influence on other chambers.

The paper at hand is part of the autonomous excavator project Thor (Terraforming Heavy Outdoor Robot) who's goal is the development of a construction machine which performs landscaping on a construction site without an operator. So far the project mainly focused on the local excavation on one position. Due to the high digging forces the machine permanently changes its position during excavation. Furthermore, the global goal is to shape the complete construction site. Therefore, a final test platform needs to permanently reposition itself on the site. Within this paper the construction site navigation function is described which guarantees safe traveling from one pose to another one. It is based on an extended A* path planning algorithm, executed on a 2D gridmap including region growing for obstacles, including forward and backward movement. In combination with an intelligent path following algorithm the machine proved to safely reach its position with the desired orientation.

The Robotics Research Lab in Kaiserserlautern, Germany, pursues the goal of automating a mobile bucket excavator for excavation and loading tasks. This document contains a short introduction to the autonomous bucket excavator THOR, a concept for low-level safety using laser scanners, and a high-level collision avoidance system using behavior-based control.

Large vertical concrete structures are still a great challenge for autonomous climbing robots, which should be able to perform different service tasks like inspection or coating of the rough surface. This paper presents a step towards a more autonomous system by introducing the behavior-based obstacle avoidance system of the wall-climbing robot CROMSCI. Main problems arise from a limited payload for environmental sensor systems, since CROMSCI uses sliding suction cups for adhesion and three wheels for locomotion. Therefore, a special sensor setup and internal representation of the environment has to be found. In this paper the overall structure of the climbing robot CROMSCI will be discussed and its sensor systems and the behavior-based components for obstacle avoidance will be shown. Experiments prove the functionality of the presented approaches under real conditions.

Wall-climbing robots are of great benefit in fields of application, which are dangerous or difficult to handle for humans. But nevertheless, most of the existing systems did not exceed experimental stadium. This paper will present the new climbing robot Crea which makes a step further from a research prototype to a device which can be applied for inspection and maintenance tasks of large concrete buildings. The system uses three driven and steerable wheels for locomotion and eleven individual adhesion chambers. The paper will introduce the hardware and software components as well as aspects for controlling and sensing and show first experimental results with this robot.

Simulation frameworks are common tools to test new algorithms or to analyze the behavior of a robot before executing the control software on the real machine. This tremendously reduces time and effort during the development process. This paper presents a component based framework for simulating different wall-climbing robots that use negative pressure adhesion in combination with a drive system. Key aspect of the simulation is the vacuum adhesion system: Surface characteristics and features in the environment influence its overall performance, which is calculated based on a thermodynamic model of the airflows. The framework tremendously improves the development process of the new wall-climbing robot CREA by the possibility to validate controllers and algorithms offline and in realtime beforehand.

Friction of sealings is a general problem for sliding wall-climbing robots using negative pressure adhesion for attraction. Tight sealings are very leak-proof but produce higher friction which has to be overcome by the locomotion system, often in terms of tracks or wheels. On the other hand loose sealings could lead to a fail of adhesion and therefore to a drop-off. This paper presents a method to optimize friction characteristics online depending on the current situation without influencing the attraction forces. The approach makes use of an inflatable and controlled rubber sealing and adjusts the air pressure via an overlaying friction controller. Experiments on the new climbing robot CREA prove the functionality and the benefit of the developed method.

CREA robot is designed to climb up concrete walls. The robot uses the suction mechanism to provide adhesion and wheel mechanism for locomotion. Eleven chambers which are connected to one common reservoir are responsible to produce adhesion force. A controller is developed to independently control each chamber while satisfying certain criteria on the safety of the robot. It is also designed to reach minimum friction between active inflatable seals and wall. In conclusion, the controller is able to successfully meet the conditions of stability, minimum friction and safety.

Since the beginning of mobile robots the developers considered safety aspects. The challenge was - and still is - to identify hazards and to find appropriate manners to react on them. This paper presents aspects concerning the safety of wall-climbing robots and discusses different types of hazards (especially those which could cause a drop-off), their impact and how they can be handled. The main challenge is to perform a safety analysis without neither sufficient knowledge about the system nor significant statistical data for evaluation. Here, a fault tree analysis of a wall-climbing robot is performed to identify bottle necks related to safety and to specify requirements to the robot's hard- and software. Finally, some suitable measures are highlighted which improve its safety tremendously.

Climbing on vertical concrete structures like bridge pylons or dams is still a great challenge for autonomous robots. This paper presents the traction- and friction control system of the wheel-driven wall-climbing robot CROMSCI and its impact on navigation safety. This robot applies negative pressure adhesion and driven wheels for propulsion. The main challenge is to produce sufficient high forces for carrying and accelerating the robot contrarily to gravity which is inhibited by different factors. Slippery of the wheels e.g. must be minimized due to abrasion and uncontrollable movements of the robotic system. This is done by measuring upcoming forces and taking them into account for a traction control system. Another problem may occur because of shear forces between the wheels lowering the transferable forces in rolling direction. Furthermore, also the seals influence robot locomotion due to a certain driving resistance. This paper will present these control elements and prove their functionality and impact on driving safety via experimental results.

Safe navigation on vertical concrete structures is still a great challenge for mobile climbing robots. Although there is a large field of application for such systems (e. g. inspection tasks, maintenance or construction) there are still no commercial robots available. The main problem is to find the optimum of applicability and safety. Applicability comes with demands for fast navigation speed, high maneuverability, easy handling by the user and high payload in terms of inspection sensors or tools for maintenance. In contrast to that, safety requires a more defensive system behavior to ensure the adhesion even under worst conditions to avoid injuries of the technical staff or damages at the system. This thesis addresses the problem of safe navigation in the range of wall-climbing robots using negative pressure adhesion in combination with a drive system. Although such systems need to be equipped with low-level control elements for balancing the adhesion force, these closed-loop controllers are not sufficient to avoid a drop-off in certain situations. Therefore, additional measures are needed to improve the system’s safety. First of all, the different hazards affecting the robot have to be examined. Especially robot tilt and robot slip need to be handled since they are the most dangerous incidents. Based on a fault tree analysis several points of action are identified to increase the robot’s safety. The existing control components of a prototypic climbing robot are extended by additional safety measures to enhance locomotion, to ensure adhesion and to reduce risks. An advanced motion control system has been developed combining several innovative methods in the range of climbing robots such as a traction control system or a closed-loop control to minimize shear forces. These measures significantly improve robot safety during locomotion. The basis of safe adhesion lies in the control elements of the negative pressure system. In contrast to known climbing robots a novel behavior-based network has been developed combining closed-loop control behaviors and deliberative components. After all, the structure and meta values of this adhesion control network are used to analyze the current state of the system. An evaluation function, which is optimized via a genetic algorithm based on training examples, allows an online prediction of upcoming risks leading to a drop-off. These risks can be caused by small surface irregularities and rough patches of the concrete ground and can neither be described sufficiently nor detected beforehand since there exists no suitable sensor system for this special application. Finally, corresponding counteractive measures are applied to prevent the robot from a drop-off. The functionality of the developed approaches and the benefit for safety is proven in real-world experiments as well as in a simulated environment. It is shown that the prototypic robot is able to detect and avoid risky patches and obstacles and that navigation safety could be improved tremendously.

The enclosing Thor (Terraforming Heavy Outdoor Robot) project’s goal is to perform typical tasks of a bucket excavator autonomously, like landscaping, mass excavation, or material transport on construction or mining sites. The paper at hand presents an approach for close interoperateration between its reactive behavior-based control approach for highly dynamic environments with a lot of disturbances and a realistic dynamic simulation of the robot for safe parameter evaluation under given time boundaries.

Terrain traversability is a common problem in outdoor robotics. The main task is to determine if the current or upcoming terrain can be overcome by the locomotion system of the robot. But, this problem increases in terms of climbing robots which do not only have a locomotion, but also an adhesion system which has to be considered. This paper addresses these aspects and presents an approach to identify and analyze important surface features and to estimate the system's behavior. Supervised learning techniques are used to classify surfaces into different categories depending on their traversability. As test-platform, a wall-climbing robot using negative pressure adhesion and an omnidirectional drive system is considered which is able to drive on flat concrete buildings.

In the range of robotics, simulation frameworks are very common. They are used to perform tests of algorithms, for optimization and to analyze the system behavior in situations, which would be hazardous or difficult for the real robot. This paper addresses a simulation framework related to a wall-climbing robot using negative pressure adhesion in combination with an omnidirectional drive system. The key aspect of this simulation is the adhesion system consisting of simulated pressure sensors, valves between adhesion chambers and vacuum reservoir and a simulated adaptive sealing proofing the vacuum chambers towards ambient air. The interaction of environmental features (e. g. surface characteristics like roughness or special geometries) and the vacuum chambers of the robot is handled by a thermodynamic model providing the basis for airflow simulation between the virtual surface and the robot. These features facilitate the validation of control algorithms and closed-loop controllers in realtime.

The maintenance and inspection of large vertical structures with autonomous systems is still an unsolved problem. A large number of different robots exist which are able to navigate on buildings, ship hulls or other human-made structures. But, most of these systems are limited to special situations or applications. This paper deals with different locomotion and adhesion methods for climbing robots and presents characteristics, challenges and applications for these systems. Based on a given set of requirements these principles are examined and in terms of a comprehensive state-of-the-art more than hundred climbing robots are presented. Finally, this schematics is applied to design aspects of a wall-climbing robot which should be able to inspect large concrete buildings.

Safe navigation on vertical concrete structures is still a great challenge for mobile climbing robots. The main problem is to find the optimum of applicability and safety since these systems have to fulfill certain tasks without endangering persons or their environment. This paper addresses aspects of safe navigation in the range of wall-climbing robots using negative pressure adhesion in combination with a drive system. In this context aspects of the developed robot control architecture will be presented and common hazards for this type of robots are examined. Based on this a risk prediction function is trained via methods of evolutionary algorithms using internal data generated inside of the behavior-based robot control network. Although there will always be a residual risk of a robot dropoff it is shown that the risk could be lowered tremendously by the developed analysis methods and counteractive measures.

Simulation frameworks are wide-spread in the range of robotics to test algorithms and analyze system behavior beforehand – which tremendously reduces effort and time needed for conducting experiments on the real machines. This paper addresses a component based framework for simulating a wall-climbing robot that uses negative pressure adhesion in combination with an omnidirectional drive system. Key aspect is the adhesion system which interacts with the environmental features such as surface characteristics (e. g. roughness) or defects. An elaborate thermodynamic model provides the basis for a realistic simulation of the airflow between the virtual environment and the vacuum chambers of the robot. These features facilitate the validation of closed-loop controllers and control algorithms offline and in realtime.