Thomas, Shawna individual record
Instructional Assistant Professor
overview

Randomized motion planning algorithms can be applied to any type of robot, from simple rigid bodies to complex articulated linkages. We abstract the particular motion planning problem into configuration space (C-space) where each point in C-space represents a particular configuration/placement of the robot. Invalid configurations (e.g., in-collision, high energy) become C-obstacles in this higher dimensional space. We then use randomized sampling to construct a graph or tree in C-space and use this data structure to extract feasible trajectories. We explore different general purpose techniques to improve planner performance as well as applications to computational biology.

education and training
selected publications
Academic Articles12
  • Motes, J., Sandstrm, R., Lee, H., Thomas, S., & Amato, N. M. (2020). Multi-Robot Task and Motion Planning With Subtask Dependencies. IEEE ROBOTICS AND AUTOMATION LETTERS. 5(2), 3338-3345.
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  • Motes, J., Sandstrm, R., Adams, W., Ogunyale, T., Thomas, S., & Amato, N. M. (2019). Interaction Templates for Multi-Robot Systems. IEEE ROBOTICS AND AUTOMATION LETTERS. 4(3), 2926-2933.
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  • Amato, N. M., Brock, O., Morales, M., & Thomas, S. (2018). Special issue on “Robotics: Science and Systems”, 2016. Autonomous Robots. 42(7), 1299-1300.
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  • Amato, N. M., Ekenna, C., Thomas, S., & Roy, N. (2018). Editorial. INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH. 37(10), 1115-1116.
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  • McMahon, T., Thomas, S., & Amato, N. M. (2018). Sampling-based motion planning with reachable volumes for high-degree-of-freedom manipulators. INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH. 37(7), 779-817.
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Conference Papers38
Institutional Repository Documents1
Email
sthomas@cse.tamu.edu
First Name
Shawna
Last Name
Thomas
mailing address
Texas A&M University; Computer Science & Engineering; 3112 TAMU
College Station, TX 77843-3112
USA