Kevin M. Peterson

Planning-based prediction for pedestrians

We present a novel approach for determining robot movements that efficiently accomplish the robots tasks while not hindering the movements of people within the environment. Our approach models the goal-directed trajectories of pedestrians using maximum entropy inverse optimal control. The advantage of this modeling approach is the generality of its learned cost function to changes in the environment and to entirely different environments. We employ the predictions of this model of pedestrian trajectories in a novel incremental planner and quantitatively show the improvement in hindrance-sensitive robot trajectory planning provided by our approach.

A Robust Approach to High-Speed Navigation for Unrehearsed Desert Terrain

This article presents a robust approach to navigating at high-speed across desert terrain. A central theme of this approach is the combination of simple ideas and components to build a capable and robust system. A pair of robots were developed which completed a 212 kilometer Grand Challenge desert race in approximately seven hours. A path-centric navigation system uses a combination of LIDAR and RADAR based perception sensors to traverse trails and avoid obstacles at speeds up to 15m/s. The onboard navigation system leverages a human based pre-planning system to improve reliability and robustness. The robots have been extensively tested, traversing over 3500 kilometers of desert trails prior to completing the challenge. This article describes the mechanisms, algorithms and testing methods used to achieve this performance.

Fast feature detection and stochastic parameter estimation of road shape using multiple LIDAR

This paper describes an algorithm for an autonomous car to identify the shape of a roadway by detecting geometric features via LIDAR. The data from multiple LIDAR are fused together to detect both obstacles as well as geometric features such as curbs, berms, and shoulders. These features identify the boundaries of the roadway and are used by a stochastic state estimator to identify the most likely road shape. This algorithm has been used successfully to allow an autonomous car to drive on paved roadways as well as on off-road trails without requiring different sets of parameters for the different domains.

Predicting Terrain Traversability from Thermal Diffusivity

This paper presents a method to predict soil traversability by estimating the thermal diffusivity of terrain using a moving, continuous-wave laser. This method differentiates between different densities of the samematerial, which visionbased methods alone cannot achieve. The bulk density of a granular material has a significant effect on both its mechanical behavior and its thermal properties. This approach fits the thermal response as effected by a laser to an analytical model that is dependent on thermal diffusivity. Experimental soil strength measurements validate that thermal diffusivity is a predictor of traversability for a given material.

Complementary Flyover and Rover Sensing for Superior Modeling of Planetary Features

This paper presents complementary flyover and surface exploration for reconnaissance of planetary point destinations, like skylights and polar crater rims, where local 3D detail matters. Recent breakthroughs in precise, safe landing enable spacecraft to touch down within a few hundred meters of target destinations. These precision trajectories provide unprecedented access to bird’s-eye views of the target site and enable a paradigm shift in terrain modeling and path planning. High-angle flyover views penetrate deep into concave features while low-angle rover perspectives provide detailed views of areas that cannot be seen in flight. By combining flyover and rover sensing in a complementary manner, coverage is improved and rover trajectory length is reduced by 40 %. Simulation results for modeling a lunar skylight are presented.

Position estimation by registration to planetary terrain

LIDAR-only and camera-only approaches to global localization in planetary environments have relied heavily on availability of elevation data. The low-resolution nature of available DEMs limits the accuracy of these methods. Availability of new high-resolution planetary imagery motivates the rover localization method presented here. The method correlates terrain appearance with orthographic imagery. A rover generates a colorized 3D model of the local terrain using a panorama of camera and LIDAR data. This model is orthographically projected onto the ground plane to create a template image. The template is then correlated with available satellite imagery to determine rover location. No prior elevation data is necessary. Experiments in simulation demonstrate 2m accuracy. This method is robust to 30° differences in lighting angle between satellite and rover imagery.

A Complete System for High-Speed Navigation of Prescribed Routes

This paper presents an approach that achieves robust high-speed navigation of prescribed routes. We present the mechatronic and software considerations that resulted in two robots that have completed over 4000 km of autonomous navigation of trails and off-road terrain at an average speed of approximately 30 km/h, with sustained top speeds of 55 km/h

A long-duration propulsive lunar landing testbed

Affordable test articles for descent and landing are crucial for developing commercial lunar landing capability. To ensure successful lunar landing, flight software must be tested over mission-length durations on hardware exhibiting dynamics analogous to those of true flight articles. Energetic and structural constraints typically preclude affordable long-duration lander tests.