10 accepted papers
Identifying the environment’s structure, through detecting core components such as rooms and walls, can facilitate several tasks fundamental for the successful operation of indoor autonomous mobile robots, including semantic environment understanding. These robots often rely on 2D occupancy maps for
Detection of anomalies and faults is a crucial ability for fully autonomous robots. This letter proposes a new deep learning-based minimally supervised method for detecting anomalies in autonomous robots. We contribute a new Variational Auto-Encoder architecture able to model very long multivariate
In several applications, autonomous mobile robots benefit from knowing the structure of the indoor environments where they operate. This knowledge can be extracted from the metric maps built (e.g., using SLAM algorithms) from the data perceived by the robots' sensors. The layout is a way to represen…
The development of good experimental methodologies for robotics takes often inspiration from general principles of experimental practice. Repeatability prescribes that experiments should involve several trials in order to guarantee that results are not achieved by chance, but are systematic, and sta…
The most tight intractability results for graph-based Multirobot Path Planning (MPP), proven recently, state that time-optimal and distance-optimal MPP problems are NP-hard on planar graphs. In this letter, we go one step further for what concerns the time-optimal objectives, and prove that such pro
The importance of communication in many multirobot information-gathering tasks requires the availability of reliable communication maps. These provide estimates of the radio signal strength and can be used to predict the presence of communication links between different locations of the environment.…
Semantic mapping for autonomous mobile robots includes the place classification task that associates semantic labels (like `corridor' or `office') to rooms perceived in indoor environments. The mainstream approaches to place classification are characterized by local reasoning, where only features re…
In multirobot exploration under centralized control, communication plays an important role in constraining the team exploration strategy. Recurrent connectivity is a way to define communication constraints for which robots must connect to a base station only when making new observations. This paper
Consider a mobile robot exploring an initially unknown school building and assume that it has already discovered some classrooms, offices, and bathrooms. What can the robot infer about the presence and the locations of other classrooms and offices in the school building? This paper makes a step towa…
We consider the problem of computing patrolling strategies under communication constraints for a team of autonomous robots employed in repeated surveillance missions on a set of predefined locations. We assume the presence of a communication infrastructure providing only some regions of the environm…