Exploration of Unknown Environments Using a Tethered Mobile Robot

Exploration with mobile robots is a well known field of research, but current solutions cannot be directly applied for tethered robots. In some applications, tethers may be very important to provide power or allow communication with the robot. This thesis presents an exploration algorithm that guarantees complete exploration of arbitrary environments within the length constraint of the tether, while keeping the tether tangle-free at all times. While a generalized algorithm that can be used with several exploration strategies is also proposed, the presented implementation uses a modified frontier-based exploration approach, where the robot chooses its next goal in the frontier between explored and unexplored regions of the environment. The main modification from standard frontier-based method is the use of a cost function to sort multiple goals in one iteration and pick the cheapest one to go to, minimizing global path length in the process. The cost is calculated in terms of path length with tether constraints accounted for. The basic idea of the algorithm is to keep an estimate of the tether configuration, including length and homotopy, and decide the next robot path based on the length difference between the current tether length and the shortest tether length at the next goal position. The length difference is then used to determine whether it is safe for the robot to take the shortest path to the goal, or whether the robot has to take a different path to the goal in the way that would put the tether back into the most optimal configuration. The maximum length difference that would still guarantee global tangle-free paths has been shown to be the circumference of the smallest expected obstacle in the environment. The presented algorithm is provable correct and was tested and evaluated using both simulations and real-world experiments. Navigation of a planar robot is done with the aid of a Simultaneous Localization and Mapping (SLAM) system, with the data being provided by the on-board LiDAR scanner. The results from conducted experiments have demonstrated that the proposed algorithm results in the total path length increase of anywhere from 30% up to to 80% compared to untethered frontier-based approach, with the exact percentage increase dependent on the complexity of the environment. It is also approximately 6 times shorter than the total path length in a conservative approach of backtracking to the base to avoid tangling

An overview of robotics and autonomous systems for harsh environments

Across a wide range of industries and applications, robotics and autonomous systems can fulfil the crucial and challenging tasks such as inspection, exploration, monitoring, drilling, sampling and mapping in areas of scientific discovery, disaster prevention, human rescue and infrastructure management, etc. However, in many situations, the associated environment is either too dangerous or inaccessible to humans. Hence, a wide range of robots have been developed and deployed to replace or aid humans in these activities. A look at these harsh environment applications of robotics demonstrate the diversity of technologies developed. This paper reviews some key application areas of robotics that involve interactions with harsh environments (such as search and rescue, space exploration, and deep-sea operations), gives an overview of the developed technologies and provides a discussion of the key trends and future directions common to many of these areas

Toward a Distributed Actuation and Cognition Means for a Miniature Soft Robot

This thesis presents components of an on-going research project aimed towards developing a miniature soft robot for urban search and rescue (USAR). The three significant contributions of the thesis are verifying the water hammer actuation previous work, developing an estimator of water hammer impulse direction from hose shape, and creating the infrastructure for distributed cognitive networks. There are many technical issues in designing soft robots, in terms of perception, actuation, cognition, power, physical structure and so on. We are focusing on actuation and cognition issues in this thesis. We investigated water hammer actuation as an alternative system which provides a continuously distributed form of actuation results from water hammer effect. It is special because it is a soft actuation method. We generated some comparison experiments and verified the benefits of the water hammer actuation, and also designed our soft robot to be hose-like in order to utilize the water hammer actuator. For the cognition part, we first addressed and verified that the shape of the hose-like robot has impact on impulse direction from the water hammer actuation. And then we implemented an emulated synthetic neural network (ESNN) to analyze the direction of the impulse from the water hammer actuation. Then in order to achieve the long-term goal, we distributed the emulated synthetic neural network onto many embedded system boards to achieve a distributed cognitive network. The distributed nodes in the network are using Bluetooth communication. In the comparison experiments between the active tether system and passive tether system, we can clearly see the benefits of active tether in momentum transfer and friction reduction. For example, in the drag test, with the water hammer actuation the burden that the tether can pull was increased by about 1.6 times. For the distributed cognitive network, we successfully built an emulated synthetic neural network on distributed embedded system boards. With the shape information as the inputs, the difference on outputs from the ESNN and the experimental results is less than 3%

PRECISE LANDING OF VTOL UAVS USING A TETHER

Unmanned Aerial Vehicles (UAVs), also known as drones, are often considered the solution to complex robotics problems. The significant freedom to explore an environment is a major reason why UAVs are a popular choice for automated solutions. UAVs, however, have a very limited flight time due to the low capacity and weight ratio of current batteries. One way to extend the vehicles\u27 flight time is to use a tether to provide power from external batteries, generators on the ground, or another vehicle. Attaching a tether to a vehicle may constrain its navigation but it may also create some opportunities for improvement of some tasks, such as landing. A tethered UAV can still explore an environment, but with some additional limitations: the tether can become wrapped around or bent by an obstacle, stopping the drone from traveling further and requiring backtracking to undo; the tether can fall loose and get caught while dragging on the ground; or the base of the tether could be mobile and the UAV needs to have a way to return to it. Most issues, like those listed above, could be solved with a vision system and various kinds of markers, but this approach could not work in situations of low light, where cameras are no longer effective. In this project, a state machine was developed to land a tethered, vertical take-off and landing (VTOL) UAV using only angles taken from both ends of the tether, the tension in the tether, and the height of the UAV. The main scenarios focused on in this project were normal operation, obstacle interference, loose tether, and a moving base. Normal operation is essentially tether guidance using the tether as a direction back to the base. The obstacle case has to determine the best action for untangling the tether. The loose tether case has to handle the loss of information given by the angle sensors, as the tether direction is no longer available. This case is performed as a last-ditched effort to find the landing pad with only a moderate chance for success. Lastly, the moving base case uses the change in the angles over time to determine the speed needed to reach the base. The software was not the only focus of this project. Two hardware components of this project were a landing platform and a matching landing gear to support the landing process. These two components were designed to aid in the precision of the landed location and to ensure that the UAV was secured in position once landed. The landing platform was designed as a passive funnel-type positioning mechanism with a depression in the center that the landing gear was designed to match. The tension of the tether is used to further lock the UAV into place when in motion. While some of this project remained theoretical, particularly the moving base case, there was flight testing performed for validation of most states of the proposed state machine. The normal operation state was effective at guiding the UAV onto the landing pad. The loose tether case was also able to land within reasonable expectations. This case was not always successful at finding the landing pad. Particular methods of increasing the likelihood of success are discussed in Future Work. The Obstacle Case was also able to be detected, but the response action has yet to be tested in full. The prior testing of velocity following can be used as proof of concept due to its simplicity. In conclusion, this project successfully developed a state machine for precisely landing a tethered UAV with no environmental knowledge or localization. Further development is necessary to improve the likelihood of landing in problematic scenarios and more testing is necessary for the system as a whole. More landing scenarios could also be researched and added as cases to the state machine to increase the robustness of the landing process. However, each current subsystem achieved some level of validation and is to be improved with future developments

Localization And Mapping Of Unknown Locations And Tunnels With Unmanned Ground Vehicles

The main goals of this research were to enhance a commercial off the shelf (COTS) software platform to support unmanned ground vehicles (UGVs) exploring the complex environment of tunnels, to test the platform within a simulation environment, and to validate the architecture through field testing. Developing this platform will enhance the U. S. Army Engineering Research and Development Center’s (ERDC’s) current capabilities and create a safe and efficient autonomous vehicle to perform the following functions within tunnels: (1) localization (e.g., position tracking) and mapping of its environment, (2) traversing varied terrains, (3) sensing the environment for objects of interest, and (4) increasing the level of autonomy of UGVs available at the ERDC. The simulation experiments were performed in the STAGE Simulator, a physics-based multi-scale numerical test bed developed by Robotic Operating System (ROS). Physical testing was conducted in Vicksburg, MS using a Coroware Explorer. Both the simulation and physical testing evaluated three SLAM algorithms, i.e., Hector SLAM, gMapping, and CORESLAM to determine the superior algorithm. The superior algorithm was then used to localize the robot to the environment and autonomously travel from a start location to a destination location. Completion of this research has increased the ERDC’s level of autonomy for UGVs from tether to tele-operated to autonomous