Fig. 1. a) Our vehicle of study is a $4 weasel ball; b) it consists entirely of a battery and slowly oscillating motor mounted to a plastic shell.Abstract-There is substantial interest controlling a group of bodies from specifications of tasks given in a high-level, humanlike language. This paper proposes a methodology that creates low-level hybrid controllers that guarantee that a group of bodies execute a high-level specified task without dynamical system modeling, precise state estimation or state feedback. We do this by exploiting the wild motions of very simple bodies in an environment connected by gates which serve as the system inputs, as opposed motors on the bodies. We present experiments using inexpensive hardware demonstrating the practical feasibility of our approach to solving tasks such as navigation, patrolling, and coverage.
Abstract-We consider the problem of determining the paths of multiple, unpredictable moving bodies in a cluttered environment using weak detection sensors that provide simple crossing information. Each sensor is a beam that, when broken, provides the direction of the crossing (one bit) and nothing else. Using a simple network of beams, the individual paths are separated and reconstructed as well as possible, up to combinatorial information about the route taken. In this setup, simple filtering algorithms are introduced, and a low-cost hardware implementation that demonstrates the practicality of the approach is shown. The results may apply in settings such as verification of multirobot system execution, surveillance and security, and unobtrusive behavioral monitoring for wildlife and the elderly.
A problem is introduced in which a moving body (robot, human, animal, vehicle, and so on) travels among obstacles and binary detection beams that connect between obstacles or barriers. Each beam can be viewed as a virtual sensor that may have many possible alternative implementations. The task is to determine the possible body paths based only on sensor observations that each simply report that a beam crossing occurred. This is a basic filtering problem encountered in many settings, under a variety of sensing modalities. Filtering methods are presented that reconstruct the set of possible paths at three levels of resolution: (1) the possible sequences of regions (bounded by beams and obstacles) visited, (2) equivalence classes of homo-topic paths, and (3) the possible numbers of times the path winds around obstacles. In the simplest case, all beams are disjoint, distinguishable, and directed. More complex cases are then considered, allowing for any amount of beams overlapping, indistinguishability, and lack of directional information. The method was implemented in simulation. An inexpensive, low-energy, easily deployable architecture was also created which implements the beam model and validates the methods of the article with experiments.
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