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For vehicles to operate in unmapped areas with some degree of autonomy, it would be useful to aggregate and store processed sensor data so that it can be used later. In this paper, a tool that records and optimizes the placement of costmap data on a persistent map is presented. The optimization takes several factors into account, including local vehicle odometry, GPS signals when available, local map consistency, deformation of map regions, and proprioceptive GPS offset error. Results illustrating the creation of maps from previously unseen regions (a 100 m × 880 m test track and a 1.2 km dirt trail) are presented, with and without GPS signals available during the creation of the maps. Finally, two examples of the use of these maps are given. First, a path is planned along roads that have been seen exactly once during the mapping phase. Secondly, the map is used for vehicle localization in the absence of GPS signals.

Mobile robots that can effectively detect chemical effluents could be useful in a variety of situations, such as disaster relief or drug sniffing. Such a robot might mimic biological systems that exhibit chemotaxis, which is movement towards or away from a chemical stimulant in the environment. Some existing robotic exploration algorithms that mimic chemotaxis suffer from the problems of getting stuck in local maxima and becoming “lost”, or unable to find the chemical if there is no initial detection. We introduce the use of the RapidCell algorithm for mobile robots exploring regions with potentially detectable chemical concentrations. The RapidCell algorithm mimics the biology behind the biased random walk of Escherichia coli (E. coli) bacteria more closely than traditional chemotaxis algorithms by simulating the chemical signaling pathways interior to the cell. For comparison, we implemented a classical chemotaxis controller and a controller based on RapidCell, then tested them in a variety of simulated and real environments (using phototaxis as a surrogate for chemotaxis). We also added simple obstacle avoidance behavior to explore how it affects the success of the algorithms. Both simulations and experiments showed that the RapidCell controller more fully explored the entire region of detectable chemical when compared with the classical controller. If there is no detectable chemical present, the RapidCell controller performs random walk in a much wider range, hence increasing the chance of encountering the chemical. We also simulated an environment with triple effluent to show that the RapidCell controller avoided being captured by the first encountered peak, which is a common issue for the classical controller. Our study demonstrates that mimicking the adapting sensory system of E. coli chemotaxis can help mobile robots to efficiently explore the environment while retaining their sensitivity to the chemical gradient.

Robotic vision has become a very popular field in recent years due to the numerous promising applications it may enhance. However, errors within the cameras and in their perception of their environment can cause applications in robotics to fail. To help correct these internal and external imperfections, stereo camera calibrations are performed. There are currently many accurate methods of camera calibration available; however, most or all of them are time consuming and labor intensive. This research seeks to automate the most labor intensive aspects of a popular calibration technique developed by Jean-Yves Bouguet. His process requires manual selection of the extreme corners of a checkerboard pattern. The modified process uses embedded LEDs in the checkerboard pattern to act as active fiducials. Images are captured of the checkerboard with the LEDs on and off in rapid succession. The difference of the two images automatically highlights the location of the four extreme corners, and these corner locations take the place of the manual selections. With this modification to the calibration routine, upwards of eighty mouse clicks are eliminated per stereo calibration. Preliminary test results indicate that accuracy is not substantially affected by the modified procedure. Improved automation to camera calibration procedures may finally penetrate the barriers to the use of calibration in practice.