Daniele Calisi

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We present an approach Io autonomous exploration of a rescue environment. Exploration is based on unexplored frontiers and navigation on a two-level approach to the robot motion problem. Our method makes use of a motion planner capable of negotiating with very fine representations of the environment, that is used to move in a cluttered scenario. A(More)
“Exploration and search” is a typical task for autonomous robots performing in rescue missions, specifically addressing the problem of exploring the environment and at the same time searching for interesting features within the environment. In this paper, we model this problem as a multi-objective exploration and search problem and present a prototype(More)
Intense efforts to define a common structure in robotic applications, both from a conceptual and from an implementation point of view, have been carried out in the last years and several frameworks have been realized for helping in developing robotic applications. However, due to the diversity of these applications, as well as of the research groups(More)
Modeling robot motion planning with uncertainty in a Bayesian framework leads to a computationally intractable stochastic control problem. We seek hypotheses that can justify a separate implementation of control, localization and planning. In the end, we reduce the stochastic control problem to path- planning in the extended space of poses x covariances;(More)
Following a person is an important task for mobile service and domestic robots in applications in which human-robot interaction is a primary requirement. In this paper we present an approach that integrates appearance models and stereo vision for efficient people tracking in domestic environments. Stereo vision helps in obtaining a very good segmentation of(More)
The need for improving the robustness and the ability to adapt to different operational conditions is a key requirement for a wider deployment of robots in many application domains. To this end, uses of contextual information have proven to be effective in many robotic applications. In this paper, we present a case study on the use of contextual information(More)
In this paper we present a framework of benchmarks for evaluating and comparing motion algorithms for autonomous mobile robots and vehicles. These benchmarks focus on real-world issues, such as uncertainty and nonholonomic constraints, and on those situations that have been proven to be critical by the past research.
The need for improving the robustness, as well as the ability to adapt to different operational conditions, is a key requirement for a wider deployment of robots in many application domains. In this paper, we present an approach to the design of robotic systems, that is based on the explicit representation of knowledge about context. The goal of the(More)