Complete automation of trajectory planning tools for material deposition/removal applications has become increasingly necessary to reduce the ldquoconcept-to-consumerrdquo timeline for rapid product introduction in industries such as the automotive industry. The work in this paper is specifically motivated by automotive spray painting. Prior developments in automated trajectory planning tools promise to reduce the time required to program the robots; however, these approaches are limited to surfaces that are either approximately planar or topologically simple (i.e., with no holes). To extend the applicability of these planning tools to nonplanar and topologically complex surfaces, currently the user has to manually segment a complex surface into simpler subsets, i.e., subsets that are approximately extruded surfaces and contain no holes. However, the complex nature of the relationships between surface segmentation and resulting output characteristics such as material deposition uniformity, process cycle time, and material waste makes the task of manually segmenting the surface difficult. In this paper, we develop a hierarchical procedure that automatically segments a surface based on surface geometry, surface topology, and path geometry to obtain topologically simple subsets that are approximately extruded surfaces. Finally, we compare the effectiveness of our segmentation with the state of the art on a few automotive surfaces in simulation.

Intelligently utilizing the frictional contact between a robot and its environment can prevent slip, maintain balance, and provide stability during a robot's motion. A contact model is first needed to enable robot control achieving these goals. The model should be both accurate and simple enough to allow further system analysis. In this paper we propose a simple parametric contact model, based on the form of the Hertz-Walton model. We experimentally demonstrate that this contact model can be effectively used to predict contact forces for linear and near-linear loading paths. Finally, we briefly discuss the applicability of the presented contact model for snake robot climbing. The control of the snake robot is based on stabilizing a sequence of set points.

Complete automation of trajectory planning tools for material deposition/removal applications has become increasingly necessary to reduce the “concept-to-consumer” timeline in product development. Segmentation of a complex automotive surfaces into topologically simple surfaces remains a barrier in the automation of trajectory generation. In this paper, we develop a novel hierarchical procedure to segment a complex automotive surface into geometrically as well as topologically simple components.

Constructing climbing behaviors for hyper-redundant robots that account for the system dynamics requires a model of robot dynamics under contact and friction. One common model, rigid-body dynamics with coulomb friction, unfortunately is both an ambiguous and inconsistent set of dynamic axioms. This paper addresses the ambiguity problem by developing an algorithm which computes the set of joint torques such that all solutions are guaranteed to produce the desired system behavior. This algorithm is applied to a type of robot climbing which we denote climbing via bracing where a hyper-redundant robot stabilizes itself against gravity by pressing outward to induce friction. By bracing with a fraction of the robot, which we term a brace the remainder of the robot remains free to move upward and brace at a higher location. A sequence of braces thus moves the robot upward.

This research is focused on developing trajectory planning tools for the automotive painting industry. The geometric complexity of automotive surfaces and the complexity of the spray patterns produced by modern paint atomizers combine to make this a challenging and interesting problem. This paper documents our efforts to develop computationally tractable analytic deposition models for electrostatic rotating bell (ESRB) atomizers, which have recently become widely used in the automotive painting industry. The models presented in this paper account for both the effects of surface curvature as well as the deposition pattern of ESRB atomizers in a computationally tractable form, enabling the development of automated trajectory generation tools. We present experimental results used to develop and validate the models, and verify the interaction between the deposition pattern, the atomizer trajectory, and the surface curvature. Limitations of the deposition model with respect to predictions of paint deposition on highly curved surfaces are discussed. Note to Practitioners-The empirical paint deposition models developed herein, which are fit to experimental data, offer a significant improvement over models that are typically used in industrial robot simulations. The improved simulation results come without the computational cost and complexity of finite element methods. The models could be incorporated, as is, into existing industrial simulation tools, provided the users are cognizant of the model limitations with respect to highly curved surfaces. Although the models are based on readily available information, incorporating the models into existing robot simulation software would likely require support from the software vendor.