Tradeoffs Between Directed and Autonomous Driving on the Mars Exploration Rovers

Biesiadecki, Jeffrey J.; Leger, Patrick C.; Maimone, Mark

doi:10.1177/0278364907073777

Cited by 68 publications

(33 citation statements)

References 20 publications

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“…Egographs [8] represent a technique for generating expressive navigation search spaces offline by precomputing layered trajectories for a discrete set of initial states. Precomputed arcs and point turns comprised the control primitive sets that were used to autonomously drive Spirit and Opportunity during the Mars Exploration Rovers (MER) mission [2]. Trajectory selection was based on a convolution on a cost or goodness map.…”

Section: Related Workmentioning

confidence: 99%

Receding Horizon Model-Predictive Control for Mobile Robot Navigation of Intricate Paths

Howard

Green

Kelly

2010

Springer Tracts in Advanced Robotics

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As mobile robots venture into more complex environments, more arbitrary feasible state-space trajectories and paths are required to move safely and efficiently. The capacity to effectively navigate such paths in the face of disturbances and changes in mobility can mean the difference between mission failure and success. This paper describes a technique for model predictive control of a mobile robot that utilizes the structure of a regional motion plan to effectively search the local continuum for an improved solution. The contribution, the receding horizon model-predictive control algorithm, specifically addresses the problem of path following and obstacle avoidance through cusps, turn-in-place, and multi-point turn maneuvers in environments where terrain shape and vehicle mobility effects are non-negligible. The technique is formulated as an optimal controller that utilizes a model-predictive trajectory generator to determine parameterized control inputs that navigate general mobile robots safely through the environment. Experimental results are presented for a a six-wheeled skid-steered field robot in natural terrain.

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Section: Related Workmentioning

confidence: 99%

Receding Horizon Model-Predictive Control for Mobile Robot Navigation of Intricate Paths

Howard

Green

Kelly

2010

Springer Tracts in Advanced Robotics

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“…These rovers have successfully demonstrated, on Mars, concepts such as visual odometry and autonomous path selection from a terrain model acquired from sensor data [10]. The main sensor suite used for terrain assessment for the MER has been passive stereo vision [11].…”

Section: Related Workmentioning

confidence: 99%

Autonomous planetary exploration using LIDAR data

Rekleitis

Bedwani

Dupuis

2009

2009 IEEE International Conference on Robotics and Automation

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Abstract-In this paper we present the approach for autonomous planetary exploration developed at the Canadian Space Agency. The goal of this work is to autonomously navigate to remote locations, well beyond the sensing horizon of the rover, with minimal interaction with a human operator. We employ LIDAR range sensors due to their accuracy, long range and robustness in the harsh lighting conditions of space. Irregular Triangular Meshes (ITMs) are used for representing the environment providing an accurate yet compact spatial representation. In this paper a novel path-planning technique through the ITM is introduced, which guides the rover through flatter terrain and safely away from obstacles. Experiments performed in CSA's Mars emulation terrain that validate our approach are also presented. I. INTRODUCTIONMobile robotics has enabled scientific breakthroughs in planetary exploration [1]. Recent accomplishments have demonstrated beyond doubt the necessity and feasibility of semi-autonomous rovers for conducting scientific exploration on other planets. Both Mars Exploration Rovers (MERs) "Spirit" and "Opportunity" have the ability to detect and avoid obstacles, picking a path that would take them along a safe trajectory. MER's have reached traverses of 300m/sol. On occasion, the rovers have had to travel to locations that were at the fringe of the horizon of their sensors or even slightly beyond.The next rover missions to Mars are the "Mars Science Laboratory" (MSL) [2] and ESA's ExoMars [3]. Both of these missions have set target traverse distances on the order of one kilometer per day. Both the MSL and ExoMars rovers are therefore expected to drive regularly a significant distance beyond the horizon of their environment sensors. Earthbased operators will therefore not know a-priori the detailed geometry of the environment and will thus not be able to select via-points for the rovers throughout their traverses.One of the key technologies that will be required is the ability to sense and model the 3D environment in which the rover has to navigate. To address the above mentioned issues, the Canadian Space Agency is developing a suite of technologies for long-range rover navigation. For the purposes of this paper, "long-range" is defined as a traverse that takes the rover beyond the horizon of the rover's environment sensors.In the next Section we discuss the state-of-the-art in robotic planetary exploration. Section II presents the overall process for planetary exploration together with a short description of our test-bed. Next we present a summary of our approach to environmental modelling, Section IV

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“…These rovers have successfully demonstrated, on Mars, concepts such as visual odometry and autonomous path selection from a terrain model acquired from sensor data [4]. The models obtained through stereo imagery are used for both automatic terrain assessment and visual odometry.…”

Section: Related Workmentioning

confidence: 99%

Experimental Results for Over-the-Horizon Planetary Exploration Using a LIDAR Sensor

Rekleitis

Bedwani

Gingras

et al. 2009

Experimental Robotics

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Summary. In this paper we present the experimental results validating the approach for autonomous planetary exploration developed by the Canadian Space Agency (CSA). The goal of this work is to autonomously navigate to remote locations, well beyond the sensing horizon of the rover, with minimal interaction with a human operator. We employ LIDAR range sensors due to their accuracy, long range and robustness in the harsh lighting conditions of space. Irregular triangular meshes (ITM) are used for representing the environment providing an accurate yet compact spatial representation. In this paper after a brief overview of the proposed approach, we discuss the terrain modelling used. A variety of experiments performed in CSA's Mars emulation terrain that validate our approach are also presented.

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Tradeoffs Between Directed and Autonomous Driving on the Mars Exploration Rovers

Cited by 68 publications

References 20 publications

Receding Horizon Model-Predictive Control for Mobile Robot Navigation of Intricate Paths

Receding Horizon Model-Predictive Control for Mobile Robot Navigation of Intricate Paths

Autonomous planetary exploration using LIDAR data

Experimental Results for Over-the-Horizon Planetary Exploration Using a LIDAR Sensor

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