In this work, we take a step towards bridging the gap between the theory of formal synthesis and its application to real-world, complex, robotic systems. In particular, we present an end-to-end approach for the automatic generation of code that implements high-level robot behaviors in a verifiably correct manner, including reaction to the possible failures of low-level actions. We start with a description of the system defined a priori. Thus, a non-expert user need only specify a high-level task. We automatically construct a formal specification, in a fragment of Linear Temporal Logic (LTL), that encodes the system's capabilities and constraints, the task, and the desired reaction to low-level failures. We then synthesize a reactive mission plan that is guaranteed to satisfy the formal specification, i.e., achieve the task's goals or correctly react to failures. Lastly, we automatically generate a state machine that instantiates the synthesized symbolic plan in software. We showcase our approach using Team ViGIR's software and Atlas humanoid robot and present lab experiments, thus demonstrating the application of formal synthesis techniques to complex robotic systems. The proposed approach has been implemented and open-sourced as a collection of Robot Operating System (ROS) packages, which are adaptable to other systems.

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.

This paper addresses the coupled navigation and control problem for fully actuated dynamical systems operating in cluttered environments. The proposed method composes local feedback control policies to address the global problem in a formally correct manner. Our contribution extends the method of sequential composition to a new class offlow-throughpolicies, which are defined for an idealized point robot that is subject to bounds on velocity and acceleration. These policies, which are defined over convex polytopes, express natural behaviors and guarantee safe trajectories while respecting system constraints. This paper presents a constructive technique for building hybrid control systems with guaranteed transitions and stability properties. Simulation results demonstrate policy-based decision making for various initial conditions.

What would it be like if we could give our robot high level commands and it would automatically execute them in a verifiably correct fashion in dynamically changing environments? This work demonstrates a method for generating continuous feedback control inputs that satisfy high-level specifications. Using a collection of continuous local feedback control policies in concert with a synthesized discrete automaton, this paper demonstrates the approach on an Ackermann-steered vehicle that satisfies the command "drive around until you find an empty parking space, then park." The system reacts to changing environmental conditions using only local information, while guaranteeing the correct high level behavior. The local policies consider the vehicle body shape as well as bounds on drive and steering velocities. The discrete automaton that invokes the local policies guarantees executions that satisfy the high-level specification based only on information about the current availability of the nearest parking space. This paper also demonstrates coordination of two vehicles using the approach.

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.

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.

This paper develops a method of composing simple control policies, applicable over a limited region in a dynamical system's free space, such that the resulting composition completely solves the navigation and control problem for the given system operating in a constrained environment. The resulting control policy deployment induces a global control policy that brings the system to the goal, provided that there is a single connected component of the free space containing both the start and goal configurations. In this paper, control policies for both kinematic and simple dynamical systems are developed. This work assumes that the initial velocities are somewhat aligned with the desired velocity vector field. We conclude by offering an outline of an approach for accommodating arbitrary dynamical constraints and initial conditions.

As part of an ongoing collaborative effort with the Ford Motor Company, our research aims to develop practical and efficient trajectory planning tools for automotive painting. This paper documents our efforts to develop analytic deposition models for electrostatic rotating bell (ESRB) atomizers, which have recently become widely used in the automotive painting industry. Conventional deposition models, used in earlier automatic trajectory planning tools, fail to capture the complexity of deposition patterns generated by ESRB atomizers. The models presented here take into account both the surface curvature and the deposition pattern of ESRB atomizers, enabling planning tools to optimize trajectories to meet several measures of quality, such as coating uniformity. In addition to the development of our models, we present experimental results used to evaluate our models, and verify the interaction between the deposition pattern, trajectory, and surface curvature.