Search and rescue mobile robots have shown great promise and have been under development by the robotics researchers for many years. They are many locomotion methods for different robotic platforms, including legged, wheeled, flying and hybrid. In general, the environment that these robots would operate in is very hazardous and complicated, where wheeled robots will have difficulty physically traversing and where legged robots would need to spend too much time planning their foot placement. Drawing inspiration from biology, we have noticed that the snake is an animal well-suited to complicated, rubble filled environments. A snake’s body has a very simple structure that nevertheless allows the snake to traverse very complex environments smoothly and flexibly using different locomotion modes. Many researchers have developed different kinds of snake robots, but there is still a big discrepancy between the capabilities of current snake robots and natural snakes. Two aspects of this discrepancy are the rigidity of current snake robots, which limit their physical flexibility, and the current techniques for control and motion planning, which are too complicated to apply to these snake robots without a tremendous amount of computation time and expensive hardware. In order to bridge the gap in flexibility, pneumatic soft robotics is a potential good solution. A soft body can absorb the impact forces during the collisions with obstacles, making soft snake robots suitable for unpredictable environments. However, the incorporation of autonomous control in soft mobile robotics has not been achieved yet. One reason for this is the lack of the embeddable flexible soft body sensor technology and portable power sources that would allow soft robotic systems to meet the essential hardware prerequisites of autonomous systems. The infinite degree of freedom and fluid-dynamic effects inherent of soft pneumatics make these systems difficult in terms of modeling, control, and motion planning: techniques generally required for autonomous systems. This dissertation addresses fundamental challenges of soft robotics modeling, control, and motion planning, as well as the challenge of making an effective soft pneumatic snake platform. In my 5 years of PhD work, I have developed four generations of pressure operated WPI soft robotics snakes (SRS), the fastest of which can travel about 220 mm/s, which is around one body per second. In order to make these soft robots autonomous, I first proposed a mathematical dynamical model for the WPI SRS and verified its accuracy through experimentation. Then I designed and fabricated a curvature sensor to be embedded inside each soft actuator to measure their bending angles. The latest WPI SRS is a modularized system which can be scaled up or down depending on the requirements of the task. I also developed and implemented an algorithm which allows this version of the WPI SRS to correct its own locomotion using iterative learning control. Finally, I developed and tested a motion planning and trajectory following algorithm, which allowed the latest WPI SRS to traverse an obstacle filled environment. Future research will focus on motion planning and control of the WPI SRS in outdoor environments utilizing the camera instead of the tracking system. In addition, it is important to investigate optimal control and motion planning strategies for mobile manipulation tasks where the SRS needs to move and manipulate its environment.. Finally, the future work will include the design, control, and motion planning for a soft snake robot where each segment has two degrees-of-freedom, allowing it to lift itself off the ground and traverse complex-real-world environments.
| Identifer | oai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-dissertations-1551 |
| Date | 19 August 2017 |
| Creators | Luo, Ming |
| Contributors | Cagdas D. Onal, Advisor, Jie Fu, Committee Member, Nima Rahbar, Committee Member, Gregory S. Fischer, Committee Member |
| Publisher | Digital WPI |
| Source Sets | Worcester Polytechnic Institute |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Doctoral Dissertations (All Dissertations, All Years) |
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