Engineering topics
Publications and source records attributed to Manduchi, R..
This end-to-end obstacle negotiation system is envisioned to be useful in optimized path planning and vehicle navigation in terrain conditions cluttered with vegetation, bushes, rocks, etc. Results on natural terrain with various natural materials are presented.
In this paper we present an algorithm for adaptive resolution integration of 3D data collected from multiple distributed sensors. The input to the algorithm is a set of 3D surface points and associated sensor models. Using a probabilistic rule, a surface probability function is generated that represents the probability that a particular volume of space contains the surface. The surface probability function is represented using an octree data structure; regions of space with samples of large conariance are stored at a coarser level than regions of space containing samples with smaller covariance. The algorithm outputs an adaptive resolution surface generated by connecting points that lie on the ridge of surface probability with triangles scaled to match the local discretization of space given by the algorithm, we present results from 3D data generated by scanning lidar and structure from motion.
Obstacle detection is one of the main components of the control system of autonomous vehicles. In the case of indoor/urban navigation, obstacles are typically defined as surface points that are higher than the ground plane. This characterization, however, cannot be used in cross-country and unstructured environments, where the notion of ground plane is often not meaningful.
In this paper we introduce a general framework for an image based autonomous rock detection process for Martian terrain. A rock detection algorithm, based on this framework, is described and demonstrated on examples of real Mars Rover data. An attempt is made to produce a system that is independent of parameters to ease on-board implementation for real time in-situ operation.
The science return from future robotic exploration of the Martian surface can be enhanced by performing routine processing using on board computers.
We present a statistical analysis of the range data produced by a single-axis ladar in different situations, including the case of an obstacle partially occluded by grass.
The Demo III program has as its primary focus the development of autonomous mobility for a small rugged cross country vehicle. In this paper we report recent progress on both stereo-based obstacle detection and terrain cover color-based classification.
We propose an algorithm for texture segmentation based on a divide-and-conquer strategy of statistical modeling.
A problem of using mixture-of-Gaussian models for unsupervised texture segmentation is that multimodal textures cannot be well represented by a single Gaussian cluster.
We present an integrated system for the intelligent progressive transmission of data for deep space communications.
A common method for texture representation is to use the marginal probability densities over the outputs of a set of multi-orientation, multi-scale filters as a description of the texture.
Stereo correspondance is hard because different image features can look alike.