This paper reports outcomes of recent field deployments of the solar-powered Cool Robot, which was developed as an autonomous platform for towing or carrying scientific instruments in Greenland and Antarctica. This simple 70-kg four-wheel drive, solar-electric vehicle executes autonomous surveys via GPS waypoint following, while towing or carrying payloads of over 40 kg. Cool Robot conducted over 175 km of autonomous surveys to study atmospheric chemistry at the snow-air interface in the vicinity of Summit camp. The robot also conducted local grid surveys of the Summit ice layer in order to evaluate the potential of using ground penetrating radar to estimate the density of melt channels in the ice layer. Our key objectives were to demonstrate the operational value of a rover to locate subsurface features and the use of autonomous rovers in collecting scientific data from long-duration surveys. The Cool Robot operated reliably at -30 C, and demonstrated good oversnow mobility and adequate GPS accuracy for waypoint-following on a 5-10 meter grid. The deployment results demonstrate that autonomous vehicles have great potential to improve the efficiency of polar science.

Autonomous rover for polar science support and remote sensing

Sample collection is a common task for mobile robots and there are a variety of manipulators available to perform this operation. This thesis presents a novel scoop sample collection system design which is able to both collect and contain a sample using the same hardware. To ease the operator burden during sampling the scoop system is paired with new semi-autonomous and fully autonomous collection techniques. These are derived from data provided by colored 3D point clouds produced via image-based 3D reconstructions. A custom robotic mobility platform, the Scoopbot, is introduced to perform completely automated imaging of the sampling area and also to pick up the desired sample. The Scoopbot is wirelessly controlled by a base station computer which runs software to create and analyze the 3D point cloud models. Relevant sample parameters, such as dimensions and volume, are calculated from the reconstruction and reported to the operator. During tests of the system in full (48 images) and fast (6-8 images) modes the Scoopbot was able to identify and retrieve a sample without any human intervention. Finally, a new building crack detection algorithm (CDA) is created to use the 3D point cloud outputs from image sets gathered by a mobile robot. The CDA was shown to successfully identify and color-code several cracks in a full-scale concrete building element.

Autonomous Sample Collection Using Image-Based 3D Reconstructions

Autonomous robots in the Arctic cover a number of strategically important tasks, including climate research, reconnaissance, transportation, material delivery, search and rescue. These goals require adapting standard navigation, localization and mapping algorithms to the harsh Arctic conditions, which do not allow their straightforward usage. The paper describes main problems of using simultaneous localization and mapping (SLAM) algorithms in the Arctic region and formulate requirements for the Arctic landscape simulator. With regard to these requirements we constructed Arctic terrains in Gazebo simulator, which implemented three of the eight proposed Arctic features, and studied behavior of ROS implementations of GMapping, Hector SLAM, ORB-SLAM2 and RTAB-Map SLAM algorithms within the obtained terrains.

On the Problems of SLAM Simulation for Mobile Robots in the Arctic Conditions

The need for spider inspired robots and requirements for such robot leg footpads is discussed. The adhesion principle of natural and artificial climber footpads is evaluated. Possibility of making nature inspired structures is compared to resolution restrictions of 3D printers. Possible impact on energy saving is overviewed. Directions and methods for further research on the topic are determined.

Exploring the possibility and need of making a spider inspired footpad for robotic legs using a 3D printer for use in a low energy system

In extreme environment regions, unmanned rovers equipped with various sensors and devices are being developed for long-term exploration on behalf of humans. On the other hand, due to the harsh weather conditions and rough terrain, the rover camera has limited visible distance and field of view. Therefore, the rover cameras should be located for safe navigation and efficient terrain mapping. In this regard, to minimize the cost and time to manufacture the camera system on a rover, the simulation method using the rover design is presented to optimize the camera locations on the rover efficiently. In the simulation, a simulated terrain was taken from cameras with different locations and angles. The visible distance and overlapped extent of camera images, and terrain data accuracy calculated from the simulation were compared to determine the optimal locations of the rover's cameras. The simulated results will be used to manufacture a rover and camera system. In addition, self and system calibrations will be conducted to calculate the accurate position of the camera system on the rover.

Development of Simulation Method to Design Rover’s Camera System for Extreme Region Exploration

: A 25-kg, dual-track robot was built to satisfy the sampling protocol for surface explosives residues in soils. A rotary-tube cutter takes fairly consistent samples in a variety of soil conditions. Each sample bag holds about 30 samples to form a composite that represents the sampled area. An onboard carousel holds six bags: five composite samples and a sixth bag to clean the tube to minimize cross-contamination. We designed the robot to operate autonomously to collect a composite sample, log the coordinates of the area sampled, complete a composite within about 20 minutes, and operate without intervention for about 2 hours. A person may tele-operate the robot between sampling areas and to and from a base station where batteries and sample bags may be replenished.

/pdf/semi-autonomous-robotic-sampler-for-explosives-residues-in-2ke2823fik.pdf

Semi-Autonomous Robotic Sampler for Explosives Residues in Surface Soils

Polar robot design for performance reliability

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Autonomous rover for polar science support and remote sensing

Semi-Autonomous Robotic Sampler for Explosives Residues in Surface Soils

Polar robot design for performance reliability