Efficient customisable dynamic motion planning for assistive robots in complex human environments

Colombo, Alessio; Fontanelli, Daniele; Legay, Axel; Palopoli, Luigi; Sedwards, Sean

doi:10.3233/ais-150338

Cited by 25 publications

(7 citation statements)

References 37 publications

(44 reference statements)

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“…From a technological perspective, several solutions have been proposed, such as the use of Satisfiability Modulo Theories to verify the fulfilment of defined missions [15] or model checkers [18]. Planning robotic systems has also been analysed by considering other characteristics, spanning from hardware features [23,23] to the provision of support to people with disabilities [14]. However, while these works provide FM-solutions for specific problems, less attention is usually given to making the solutions reusable, and to their evaluation from a SE perspective.…”

Section: F4 -Considering Realistic Environmentsmentioning

confidence: 99%

Mind the gap

Askarpour

Menghi²,

Belli

et al. 2020

Proceedings of the 8th International Conference on Formal Methods in Software Engineering

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In the context of robotic software, the selection of an appropriate planner is one of the most crucial software engineering decisions. Robot planners aim at computing plans (i.e., blueprint of actions) to accomplish a complex mission. While many planners have been proposed in the robotics literature, they are usually evaluated on showcase examples, making hard to understand whether they can be effectively (re)used for realising complex missions, with heterogeneous robots, and in real-world scenarios. In this paper we propose ENFORCE, a framework which allows wrapping FM-based planners into comprehensive software engineering tools, and considers complex robotic missions. ENFORCE relies on (i) realistic maps (e.g, fire escape maps) that describe the environment in which the robots are deployed; (ii) temporal logic for mission specification; and (iii) Uppaal model checker to compute plans that satisfy mission specifications. We evaluated ENFORCE by analyzing how it supports computing plans in real case scenarios, and by evaluating the generated plans in simulated and real environments. The results show that while ENFORCE is adequate for handling single-robot applications, the state explosion still represents a major barrier for reusing existing planners in multi-robot applications.

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Section: F4 -Considering Realistic Environmentsmentioning

confidence: 99%

Mind the gap

Askarpour

Menghi²,

Belli

et al. 2020

Proceedings of the 8th International Conference on Formal Methods in Software Engineering

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“…In the context of motion planning for assisted living [16], [17], the Plasma Lab platform for Statistical Model checking (SMC) was integrated with robotic devices in the DALi and ACANTO EU projects. There, a novel online motion planning application of SMC helps those with impaired ability to negotiate complex crowded environments like shopping malls and museums.…”

Section: Statistical Model Checking and Aalmentioning

confidence: 99%

Analyzing ambient assisted living solutions: A research perspective

Kunnappilly

Legay

Margaria

et al. 2017

2017 12th International Conference on Design &Amp; Technology of Integrated Systems in Nanoscale Era (DTIS)

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Typical AAL solutions rely on integrating capabilities for health monitoring, fall detection, communication and social inclusion, supervised physical exercises, vocal interfaces, robotic platforms etc. Ensuring the safe function and quality of service with respect to various extra-functional requirements like timing and security of such AAL solutions is of highest importance. To facilitate analysis, latest system development platforms provide underlying infrastructures for model-driven design (e.g., via the DIME tool), timing and resource-usage specification (e.g., via the REMES tool), security features (e.g., by employing SECube), and statistical model-checking techniques (e.g, via Plasma). In this paper, we discuss the challenges associated with analyzing complex AAL solutions, from relevant properties to semantic interoperability issues raised by employing various frameworks for modeling and analysis, and applicability to evolving architectures. We take as examples two of the prominent existing AAL architectures and our own prior experience.

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“…The techniques proposed in the paper target a large class of robotic devices that can be used for this purpose, even though we will make explicit reference to a specific intelligent robotic walker, the FriWalk developed in the context of the European project ACANTO [1] (see Figure 1). The FriWalk is a standard commercial walking aid endowed with sensing abilities to understand the surroundings, with communication abilities to connect to cloud services and with planning abilities to produce safe paths in the environment [2]. The specific problem considered here is the so called reactive planning, which is used when a senior user of the robotic walker encounters an unforeseen obstacle while following a planned trajectory (hereinafter global path, GP).…”

Section: Introductionmentioning

confidence: 99%

Reactive Planning for Assistive Robots

Bevilacqua

Frego

Fontanelli

et al. 2018

IEEE Robot. Autom. Lett.

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We consider a vehicle consisting of a robotic walking assistant pushed by a user. The robot can guide the person along a path and suggest a velocity by various means. The vehicle moves in a crowded environment and can detect the different pedestrian in the surroundings. We propose a reactive planner that modifies the path in order to avoid the pedestrian in the surroundings. The algorithm relies on a very accurate model to predict the motion of each pedestrian, i.e. the Headed Social Force Model (HSFM). The possible trajectories for both the vehicle and the pedestrians are modelled as clothoid curves, which are efficient to manage from the numeric point of view and are very comfortable to follow for the user. Probabilistic techniques are used to account for the variability of the motion of each pedestrian. The path is efficient to generate, is collision free (up to a certain probability) and is comfortable to follow. Simulations and comparisons with a state of the art planner using real data as well as experiments are reported to prove the effectiveness of the method.

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Efficient customisable dynamic motion planning for assistive robots in complex human environments

Cited by 25 publications

References 37 publications

Mind the gap

Mind the gap

Analyzing ambient assisted living solutions: A research perspective

Reactive Planning for Assistive Robots

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