Joydeep Biswas

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This paper reviews a model of computation used in industrial practice in signal processing software environments and experimentally in other contexts. It gives this model the name “dataflow process networks,” and studies its formal properties as well as its utility as a basis for programming language design. Variants of this model are used in commercial(More)
Building upon previous work that demonstrates the effectiveness of WiFi localization information per se, in this paper we contribute a mobile robot that autonomously navigates in indoor environments using WiFi sensory data. We model the world as a WiFi signature map with geometric constraints and introduce a continuous perceptual model of the environment(More)
We research and develop autonomous mobile service robots as Collaborative Robots, i.e., CoBots. For the last three years, our four CoBots have autonomously navigated in our multi-floor office buildings for more than 1,000km, as the result of the integration of multiple perceptual, cognitive, and actuations representations and algorithms. In this paper, we(More)
Several researchers, present authors included, envision personal mobile robot agents that can assist humans in their daily tasks. Despite many advances in robotics, such mobile robot agents still face many limitations in their perception, cognition, and action capabilities. In this work, we propose a symbiotic interaction between robot agents and humans to(More)
The sheer volume of data generated by depth cameras provides a challenge to process in real time, in particular when used for indoor mobile robot localization and navigation. We introduce the Fast Sampling Plane Filtering (FSPF) algorithm to reduce the volume of the 3D point cloud by sampling points from the depth image, and classifying local grouped sets(More)
Although since the days of the Shakey robot, there have been a rich variety of mobile robots, we realize that there were still no general autonomous, unsupervised mobile robots servicing users in our buildings. In this paper, we contribute the algorithms and results of our successful deployment of a service mobile robot agent, CoBot, in our multi-floor(More)
For the last three years, we have developed and researched multiple collaborative robots, CoBots, which have been autonomously traversing our multi-floor buildings. We pursue the goal of long-term autonomy for indoor service mobile robots as the ability for them to be deployed indefinitely while they perform tasks in an evolving environment. The CoBots(More)
In this video we briefly illustrate the progress and contributions made with our mobile, indoor, service robots CoBots (Collaborative Robots), since their creation in 2009. Many researchers, present authors included, aim for autonomous mobile robots that robustly perform service tasks for humans in our indoor environments. The efforts towards this goal have(More)
On 18 November 2014, a team of four autonomous CoBot robots reached 1,000-km of overall autonomous navigation, as a result of a 1,000-km challenge that the authors had set three years earlier. The authors are frequently asked for the lessons learned, as well as the performance results. In this article, they introduce the challenge and contribute a detailed(More)
Particle filters for mobile robot localization must balance computational requirements and accuracy of localization. Increasing the number of particles in a particle filter improves accuracy, but also increases the computational requirements. Hence, we investigate a different paradigm to better utilize particles than to increase their numbers. To this end,(More)