Search-based versus Sampling-based Robot Motion Planning: A Comparative Study

Robot motion planning is a challenging domain as it involves dealing with high-dimensional and continuous search space. In past decades, a wide variety of planning algorithms have been developed to tackle this problem, sometimes in isolation without comparing to each other. In this study, we benchmark two such prominent types of algorithms: OMPL's sampling-based RRT-Connect and SMPL's search-based ARA* with motion primitives. To compare these two fundamentally different approaches fairly, we adapt them to ensure the same planning conditions and benchmark them on the same set of planning scenarios. Our findings suggest that sampling-based planners like RRT-Connect show more consistent performance across the board in high-dimensional spaces, whereas search-based planners like ARA* have the capacity to perform significantly better when used with a suitable action-space sampling scheme. Through this study, we hope to showcase the effort required to properly benchmark motion planners from different paradigms thereby contributing to a more nuanced understanding of their capabilities and limitations. The code is available at https://github.com/gsotirchos/benchmarking_plannersComment: presented at ICAPS 2024 workshop PlanRo

Quantitative morphometric analysis of a river basin using GIS techniques: Case study of Miljacka River, Bosnia and Herzegovina

This paper concerns the analysis of the morphometric characteristics of the Miljacka river basin using the Digital Elevation Model of the terrain in the Geographical Information System. A quantitative geomorphological analysis of general characteristics was performed, whereby the analysis was supplemented with specific parameters of the drainage system, which are of linear, areal and relief characteristics. Standard mathematical formulas and software tools for Surface and Hydrology in the GIS software environment were used to estimate the mentioned parameters, using ArcMap 10.4. By working in the Arc Map program, a database system was created, with the use of a grid system, which offers the possibility of overlaying geospatial data, extracting certain parameters and their analysis and synthesis. The analyzed parameters are indicators of the shape and recent processes in the relief. They represent a supplement in the inventory and typification of relief forms, which, thanks to GIS software, have a geographic reference, which facilitates their correlation. The importance of the conducted analysis is reflected in the fact that the obtained data have a numerical value, are verifiable and can be applied multiple times in practice for the purposes of determining erosive processes, protecting and improving space and the living environment, solving water management problems, planning economic activities and drafting spatial plans

Cognitive absorption and the behavioral intention to use business intelligence: Determinants and influence of cognitive absorption

Introduction: In the last decade Business intelligence became increasingly important for organizations to adopt in order to compete in highly changing industries. The main purpose of the business intelligence system is to enable users to make and execute decisions better and faster. However, the success of business intelligence is not guaranteed. Users are defined as one of the main sources of the potential issues, since they are the ones who should incorporate the new system into their work environment. Users interact with the system via business intelligence application, and for that reason, it is important to investigate users' behavioral intentions towards the application. In order to investigate users intentions, several theoretical constructs have been developed, mostly from the technology acceptance research. The main one being explored in this study is cognitive absorption. Purpose: The purpose of this study is to test the theory presented in Agarwal and Karahanna (2000) in the new setting. The authors’ theory proved the influence of the cognitive absorption in the context of the World Wide Web. We will use their theory in order to investigate the determinants and the influence of the cognitive absorption in the business intelligence context. Method: This study is explanatory in nature. We used survey methodology - questionnaire for the hypotheses testing. We tested seven hypotheses based on the theoretical model adapted from the literature. Several statistical analyses have been conducted for measurement and hypotheses testing, and they have been performed in SPSS and SmartPLS software packages. Conclusion: The results of the analysis identified playfulness as the significant determinant of the cognitive absorption with the business intelligence application. Furthermore, cognitive absorption proved to have the significant direct as well as indirect influence on the behavioral intention to use the business intelligence application

WHICH HOTEL ATTRIBUTES MATTER FOR MASS TOURIST: A QUALITATIVE RESEARCH ON TOURISTS’ REVIEW ON TRIP ADVISOR

Development of Internet and especially Web2.0 technologies introduced numerous opportunities for tourism industry. Due to new web-based platforms where customers can buy, evaluate and comment the products and/or services, Internet has become an important source of data that can be used in academic research. Therefore, the researchers of this paper aimed to determine the most important attributes that affect hotel choice based on the comments on one of the world’s most popular online travel platforms-Trip Advisor. In the scope of the research are reviews and comments on hotels found in touristic center of Belek in one of the most popular mass tourism destinations – Antalya. As a result of the content analysis, there are three groups of attributes which matter for mass tourists in terms of their hotel choice: attributes regarding destination, service and hotel, with attributes under the service category representing the most dominant ones in terms of hotel choice. The results of this research may be useful to hotel investors and potential hotel guests as well contribute to the overall knowledge about online travel behavior and preferences

SLOPE: Search with Learned Optimal Pruning-based Expansion

Heuristic search is often used for motion planning and pathfinding problems, for finding the shortest path in a graph while also promising completeness and optimal efficiency. The drawback is it's space complexity, specifically storing all expanded child nodes in memory and sorting large lists of active nodes, which can be a problem in real-time scenarios with limited on-board computation. To combat this, we present the Search with Learned Optimal Pruning-based Expansion (SLOPE), which, learns the distance of a node from a possible optimal path, unlike other approaches that learn a cost-to-go value. The unfavored nodes are then pruned according to the said distance, which in turn reduces the size of the open list. This ensures that the search explores only the region close to optimal paths while lowering memory and computational costs. Unlike traditional learning methods, our approach is orthogonal to estimating cost-to-go heuristics, offering a complementary strategy for improving search efficiency. We demonstrate the effectiveness of our approach evaluating it as a standalone search method and in conjunction with learned heuristic functions, achieving comparable-or-better node expansion metrics, while lowering the number of child nodes in the open list. Our code is available at https://github.com/dbokan1/SLOPE.Comment: presented at the ICAPS 2024 workshop on Bridging the Planning and Reinforcement Learnin

On the Future of Passenger Mobility and its Greenhouse Gas Emissions in Cities: Scenarios for Different Types of Policies

Many cities have set goals for reducing greenhouse gas emissions. Mobility is a major target sector as it is still widely fossil fuel-dependent and largely car-oriented. In this paper, a new methodological approach for modelling the impact of different policies on mobility, energy demand and resulting flow and embedded greenhouse gas emissions from vehicles is derived up to 2050. Finally, this approach is applied to the case of the City of Vienna. Three scenarios are developed with different policy targets focusing on battery electric vehicles and public transport. Each scenario was calculated with an average mix of electricity and a mix of renewable energy sources to be reached by 2030. The major conclusions are: (i) The impact of policies is of tremendous importance; (ii) Travel activity must be reduced and (iii) Public transport must be supported (iv) The electricity mix has to be switched to renewable energy sources