A practical autonomous path planner for turn-of-the-century planetary microrovers

With the success of Mars Pathfinder's Sojourner rover, a new era of planetary exploration has opened, with demand for highly capable mobile robots. These robots must be able to traverse long distances over rough, unknown terrain autonomously, under severe resource constraints. Based on the authors' firsthand experience with the Mars Pathfinder mission, this paper reviews issues which are critical for successful autonomous navigation of planetary rovers. No currently proposed methodology addresses all of these issues. We next report on the 'Wedgebug' algorithm, which is applicable to planetary rover navigation in SE(2). The Wedgebug algorithm is complete, correct, requires minimal memory for storage of its worked model, and uses only on-board sensors, which are guided by the algorithm to efficiently senses only the data needed for motion planning. The implementation of a version of Wedgebug on the Rocky7 Mars Rover prototype at the Jet Propulsion Laboratory is described, and experimental results from operation in simulated martian terrain are presented

A practical autonomous path planner for turn-of-the-century planetary microrovers

With the success of Mars Pathfinder's Sojourner rover, a new era of planetary exploration has opened, with demand for highly capable mobile robots. These robots must be able to traverse long distances over rough, unknown terrain autonomously, under severe resource constraints. Based on the authors' firsthand experience with the Mars Pathfinder mission, this paper reviews issues which are critical for successful autonomous navigation of planetary rovers. No currently proposed methodology addresses all of these issues. We next report on the 'Wedgebug' algorithm, which is applicable to planetary rover navigation in SE(2). The Wedgebug algorithm is complete, correct, requires minimal memory for storage of its worked model, and uses only on-board sensors, which are guided by the algorithm to efficiently senses only the data needed for motion planning. The implementation of a version of Wedgebug on the Rocky7 Mars Rover prototype at the Jet Propulsion Laboratory is described, and experimental results from operation in simulated martian terrain are presented

Stereo-vision-based navigation of a six-legged walking robot in unknown rough terrain

In this paper we presents a visual navigation algorithm for the six-legged walking robot DLR Crawler in rough terrain. The algorithm is based on stereo images from which depth images are computed using the semi- global matching (SGM) method. Further, a visual odometry is calculated along with an error measure. Pose estimates are obtained by fusing iner- tial data with relative leg odometry and visual odometry measurements using an indirect information filter. The visual odometry error measure is used in the filtering process to put lower weights on erroneous visual odometry data, hence, improving the robustness of pose estimation. From the estimated poses and the depth images, a dense digital terrain map is created by applying the locus method. The traversability of the terrain is estimated by a plane fitting approach and paths are planned using a D* Lite planner taking the traversability of the terrain and the current motion capabilities of the robot into account. Motion commands and the traversability measures of the upcoming terrain are sent to the walking layer of the robot so that it can choose an appropriate gait for the terrain. Experimental results show the accuracy of the navigation algorithm and its robustness against visual disturbances

Rough-terrain mobile robot planning and control with application to planetary exploration

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2001.Includes bibliographical references (leaves 119-130).Future planetary exploration missions will require mobile robots to perform difficult tasks in highly challenging terrain, with limited human supervision. Current motion planning and control algorithms are not well suited to rough-terrain mobility, since they generally do not consider the physical characteristics of the rover and its environment. Failure to understand these characteristics could lead to rover entrapment and mission failure. In this thesis, methods are presented for improved rough-terrain mobile robot mobility, which exploit fundamental physical models of the rover and terrain. Wheel-terrain interaction has been shown to be critical to rough terrain mobility. A wheel-terrain interaction model is presented, and a method for on-line estimation of important model parameters is proposed. The local terrain profile also strongly influences robot mobility. A method for on-line estimation of wheel-terrain contact angles is presented. Simulation and experimental results show that wheel-terrain model parameters and contact angles can be estimated on-line with good accuracy. Two rough-terrain planning algorithms are introduced. First, a motion planning algorithm is presented that is computationally efficient and considers uncertainty in rover sensing and localization. Next, an algorithm for geometrically reconfiguring the rover kinematic structure to optimize tipover stability margin is presented. Both methods utilize models developed earlier in the thesis.(cont.) Simulation and experimental results on the Jet Propulsion Laboratory Sample Return Rover show that the algorithms allow highly stable, semi-autonomous mobility in rough terrain. Finally, a rough-terrain control algorithm is presented that exploits the actuator redundancy found in multi-wheeled mobile robots to improve ground traction and reduce power consumption. The algorithm uses models developed earlier in the thesis. Simulation and experimental results show that the algorithm leads to improved wheel thrust and thus increased mobility in rough terrain.by Karl David Iagnemma.Ph.D

An autonomous path planner implemented on the rocky7 prototype microrover

Much prior work in mobile robot path planning har been based on assumptions that are not really applicable for exploration of planetary terrains. Based on the first author’s experience with the recent Mars Pathfinder mission, this paper reviews the issues that are critical for successful autonomous navigation of planetary rovers. No currently proposed methodology accurately addresses ali of these issues. We next report on an extension of the recently proposed “Tangent Bug ” algorithm. The implementation of this extended algorithm on the Rocky 7 Mars Rover prototype at the Jet Propulsion Laboratory is described, and experimental results are presented. In addition, experience with the limitations encountered by the Sojourner rover in actual Marh’an terrain suggest that terrain traversability must be more accurately handled in autonomous planning algorithms for interplanetary rovers. 1