A survey on the design space of end-user-oriented languages for specifying robotic missions

Mobile robots are becoming increasingly important in society. Fulfilling complex missions in different contexts and environments, robots are promising instruments to support our everyday live. As such, the task of defining the robot’s mission is moving from professional developers and roboticists to the end-users. However, with the current state-of-the-art, defining missions is non-trivial and typically requires dedicated programming skills. Since end-users usually lack such skills, many commercial robots are nowadays equipped with environments and domain-specific languages tailored for end-users. As such, the software support for defining missions is becoming an increasingly relevant criterion when buying or choosing robots. Improving these environments and languages for specifying missions toward simplicity and flexibility is crucial. To this end, we need to improve our empirical understanding of the current state-of-the-art of such languages and their environments. In this paper, we contribute in this direction. We present a survey of 30 mission specification environments for mobile robots that come with a visual and end-user-oriented language. We explore the design space of these languages and their environments, identify their concepts, and organize them as features in a feature model. We believe that our results are valuable to practitioners and researchers designing the next generation of mission specification languages in the vibrant domain of mobile robots.

Reactive sampling-based path planning with temporal logic specifications

We develop a sampling-based motion planning algorithm that combines long-term temporal logic goals with short-term reactive requirements. The mission specification has two parts: (1) a global specification given as a linear temporal logic (LTL) formula over a set of static service requests that occur at the regions of a known environment, and (2) a local specification that requires servicing a set of dynamic requests that can be sensed locally during the execution. The proposed computational framework consists of two main ingredients: (a) an off-line sampling-based algorithm for the construction of a global transition system that contains a path satisfying the LTL formula; and (b) an on-line sampling-based algorithm to generate paths that service the local requests, while making sure that the satisfaction of the global specification is not affected. The off-line algorithm has four main features. First, it is incremental, in the sense that the procedure for finding a satisfying path at each iteration scales only with the number of new samples generated at that iteration. Second, the underlying graph is sparse, which implies low complexity for the overall method. Third, it is probabilistically complete. Fourth, under some mild assumptions, it has the best possible complexity bound. The on-line algorithm leverages ideas from LTL monitoring and potential functions to ensure progress towards the satisfaction of the global specification while servicing locally sensed requests. Examples and experimental trials illustrating the usefulness and the performance of the framework are included.

Building the executive system of autonomous aerial robots using the Aerostack open-source framework

A variety of open-source software tools are currently available to help building autonomous mobile robots. These tools have proven their effectiveness in developing different types of robotic systems, but there are still needs related to safety and efficiency that are not sufficiently covered. This article describes recent advances in the Aerostack software framework to address part of these needs, which may become critical in the case of aerial robots. The article describes a software tool that helps to develop the executive system, an important component of the control architecture whose characteristics significantly affect the quality of the final autonomous robotic system. The presented tool uses an original solution for execution control that aims at simplifying mission specification and protecting against errors, considering also the efficiency needs of aerial robots. The effectiveness of the tool was evaluated by building an experimental autonomous robot. The results of the evaluation show that it provides significant benefits about usability and reliability with acceptable development effort and computational cost. The tool is based on Robot Operating System and it is publicly available as part of the last release of the Aerostack software framework (version 3.0).

Robot Mission Planning using Co-evolutionary Optimization

SummaryMission planning is a complex motion planning problem specified by using Temporal Logic constituting of Boolean and temporal operators, typically solved by model verification algorithms with an exponential complexity. The paper proposes co-evolutionary optimization thus building an iterative solution to the problem. The language for mission specification is generic enough to represent everyday missions, while specific enough to design heuristics. The mission is broken into components which cooperate with each other. The experiments confirm that the robot is able to outperform the search, evolutionary and model verification techniques. The results are demonstrated by using a Pioneer LX robot.

Context/Resource-Aware Mission Planning Based on BNs and Concurrent MDPs for Autonomous UAVs

This paper presents a scalable approach to model uncertainties within a UAV (Unmanned Aerial Vehicle) embedded mission manager. It proposes a concurrent version of BFM models, which are Bayesian Networks built from FMEA (Failure Mode and Effects Analysis) and used by MDPs (Markov Decision Processes). The models can separately handle different applications during the mission; they consider the context of the mission including external constraints (luminosity, climate, etc.), the health of the UAV (Energy, Sensor) as well as the computing resource availability including CPU (Central Processing Unit) load, FPGA (Field Programmable Gate Array) use and timing performances. The proposed solution integrates the constraints into a mission specification by means of FMEA tables in order to facilitate their specifications by non-experts. Decision-making processes are elaborated following a “just enough” quality management by automatically providing adequate implementation of the embedded applications in order to achieve the mission goals, in the context given by the sensors and the on-board monitors. We illustrate the concurrent BFM approach with a case study of a typical tracking UAV mission. This case also considers a FPGA-SoC (FPGA-System on Chip) platform into consideration and demonstrates the benefits to tune the quality of the embedded applications according to the environmental context.