Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions

Welcome to ROBOTICA 2009. This is the 9th edition of the conference on Autonomous Robot Systems and Competitions, the third time with IEEE‐Robotics and Automation Society Technical Co‐Sponsorship. Previous editions were held since 2001 in Guimarães, Aveiro, Porto, Lisboa, Coimbra and Algarve. ROBOTICA 2009 is held on the 7th May, 2009, in Castelo Branco , Portugal. ROBOTICA has received 32 paper submissions, from 10 countries, in South America, Asia and Europe. To evaluate each submission, three reviews by paper were performed by the international program committee. 23 papers were published in the proceedings and presented at the conference. Of these, 14 papers were selected for oral presentation and 9 papers were selected for poster presentation. The global acceptance ratio was 72%. After the conference, eighth papers will be published in the Portuguese journal Robótica, and the best student paper will be published in IEEE Multidisciplinary Engineering Education Magazine. Three prizes will be awarded in the conference for: the best conference paper, the best student paper and the best presentation. The last two, sponsored by the IEEE Education Society ‐ Student Activities Committee. We would like to express our thanks to all participants. First of all to the authors, whose quality work is the essence of this conference. Next, to all the members of the international program committee and reviewers, who helped us with their expertise and valuable time. We would also like to deeply thank the invited speaker, Jean Paul Laumond, LAAS‐CNRS France, for their excellent contribution in the field of humanoid robots. Finally, a word of appreciation for the hard work of the secretariat and volunteers. Our deep gratitude goes to the Scientific Organisations that kindly agreed to sponsor the Conference, and made it come true. We look forward to seeing more results of R&D work on Robotics at ROBOTICA 2010, somewhere in Portugal

Game-Theoretic Safety Assurance for Human-Centered Robotic Systems

In order for autonomous systems like robots, drones, and self-driving cars to be reliably introduced into our society, they must have the ability to actively account for safety during their operation. While safety analysis has traditionally been conducted offline for controlled environments like cages on factory floors, the much higher complexity of open, human-populated spaces like our homes, cities, and roads makes it unviable to rely on common design-time assumptions, since these may be violated once the system is deployed. Instead, the next generation of robotic technologies will need to reason about safety online, constructing high-confidence assurances informed by ongoing observations of the environment and other agents, in spite of models of them being necessarily fallible.This dissertation aims to lay down the necessary foundations to enable autonomous systems to ensure their own safety in complex, changing, and uncertain environments, by explicitly reasoning about the gap between their models and the real world. It first introduces a suite of novel robust optimal control formulations and algorithmic tools that permit tractable safety analysis in time-varying, multi-agent systems, as well as safe real-time robotic navigation in partially unknown environments; these approaches are demonstrated on large-scale unmanned air traffic simulation and physical quadrotor platforms. After this, it draws on Bayesian machine learning methods to translate model-based guarantees into high-confidence assurances, monitoring the reliability of predictive models in light of changing evidence about the physical system and surrounding agents. This principle is first applied to a general safety framework allowing the use of learning-based control (e.g. reinforcement learning) for safety-critical robotic systems such as drones, and then combined with insights from cognitive science and dynamic game theory to enable safe human-centered navigation and interaction; these techniques are showcased on physical quadrotors—flying in unmodeled wind and among human pedestrians—and simulated highway driving. The dissertation ends with a discussion of challenges and opportunities ahead, including the bridging of safety analysis and reinforcement learning and the need to ``close the loop'' around learning and adaptation in order to deploy increasingly advanced autonomous systems with confidence

Proceedings of the Conference on Production Systems and Logistics: CPSL 2022

[no abstract available

Water productivity indices of the soybean grown on silty clay soil under sprinkler irrigation

The objective of this research was to compare the effects of different irrigation treatments on soybean [Glycine max (L.) Merr.] productivity and water use efficiency on experimental fields of the Maize Research Institute of Zemun Polje(Serbia), in 2007 and 2008. Four irrigation levels were investigated: full irrigation (I100), 65% and 40% of I100 (I65 and I40) and a rain-fed (I0) system. The crop water use efficiency (CWUE, also known as crop water productivity –CWP), irrigation water use efficiency (IWUE) and evapotranspiration water use efficiency (ETWUE) were used to assess the water productivity of each studied treatment. The efficiency of the same treatment differed between the years as it depended on seasonal water availability, weather conditions and their impact on seed yields. Maximum and minimum yields were obtained in the I65 and I0 treatments, averaging 3.41 t ha–1 and 2.26 t ha–1, respectively. Water use efficiency values were influenced by the irrigation levels. In general, CWUE values increased with the increased level of irrigation. In both growing seasons, IWUE and ETWUE decreased with increasing the seasonal water consumption and irrigation depth. On average, treatments I40 and I65 resulted in similar or higher CWUE and ETWUE than I100, in both growing seasons. I65 resulted in the highest IWUE, averaged over the two seasons, while I100 had the lowest IWUE. I65 could be proper for the soybean irrigated in Vojvodina when there is no water shortage and I45 could be used as a good basis for reduced sprinkler irrigation strategy development under water shortage