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Constraint-based specification, planning and control for mobile manipulators in dynamic environments
(2024)
Assistive robots have the potential to improve human lives significantly in many different forms. The possible applications are widespread, ranging from workplace assistance to healthcare, therapy, and household applications. Mobile manipulators, combining mobility and manipulation abilities, are an especially promising type of robot for these kinds of applications. Robots operating in unstructured, human-centered environments, as well as interacting with humans, have to be able to safely and robustly deal with a dynamically changing environment and sometimes unexpected motions by humans. Creating robot motions that respect and appropriately react to any possible change in the environment is a challenging research question. It begins with the specification of the requirements for robot motions for the respective task. Both planning and reactive control are required for robust robot motions. These two approaches are not always simple to combine: following a plan often conflicts with reacting to changes and a method of reconciling them is required. This dissertation presents a method of specifying and generating robot motions for mobile manipulators based on geometric constraints. Constraints express whether the current robot position satisfies its requirements, and if not, how far off it is. Constraint rules are introduced, and are used to adapt the parameters of the constraints to changes in the environment. Constraint controllers are applied to generate reactive robot motions based on the current value of the constraints. Different types of constraints allow for different types of reactions. The concept of an action brings together multiple constraint specifications, in which priorities, tolerances, and weights are used to express the relative importance of the requirements. Besides reactive control, a method to create and safely execute motion plans for action specifications is presented. Furthermore, a method for automatically detecting when planning is required is described. In order to demonstrate the capabilities of the presented approach, it is evaluated on two different case studies. The first consists of an object handover between robot and human, the second considers a robot shining a flashlight to provide light to a human. Both case studies are evaluated in a successful case and different failure scenarios to assess the robustness of the approach.
The manufacturing industry is undergoing a significant transformation in the context of Industry 4.0, and production is shifting from mass products to individual products of batch size one. Moreover, the increasing complexity of components, e.g., due to additive manufacturing, makes the testing setups of components even more complex. Due to the low quantities of the components, it is not profitable to build test benches for each individual component to test a large number of different forces and torsions to ensure the needed product quality. In order to be able to test various components flexibly through different motions, we developed a concept to perform robot-based destructive component testing with industrial robots. The six degrees of freedom and the broad working range of an industrial robot make it possible to apply forces and torques to different products. Since industrial robots cannot apply the same forces and torques in all axis positions, a position must be calculated whe re the specimen can be tested. Therefore, we propose an approach for automatic specimen placement, which includes a format to map applicable forces and torques of industrial robots. Furthermore, we present an algorithmic approach to execute an automatic feasibility check for the required test motions and an automatic specimen placement using an exemplary robot-based component testing bench.
