The Infrared Imaging Spectrograph (IRIS) for TMT: motion planning with collision avoidance for the on-instrument wavefront sensors
Edward L. Chapin, Jennifer Dunn, Jason Weiss, Kim Gillies, Yutaka, Hayano, Chris Johnson, James Larkin, Anna Moore, Reed L. Riddle, Ji Man Sohn,, Roger Smith, Ryuji Suzuki, Gregory Walth, Shelley Wright

TL;DR
This paper presents a collision avoidance motion planning algorithm for the on-instrument wavefront sensors of the IRIS instrument on TMT, using potential fields to generate smooth, collision-free arm trajectories.
Contribution
The paper introduces a novel potential field-based motion planning method for collision avoidance in multi-arm optical sensor positioning systems.
Findings
Simulations show smooth, efficient collision-free paths.
The method effectively avoids local minima issues.
Algorithm is computationally inexpensive and suitable for real-time use.
Abstract
The InfraRed Imaging Spectrograph (IRIS) will be a first-light client instrument for the Narrow Field Infrared Adaptive Optics System (NFIRAOS) on the Thirty Meter Telescope. IRIS includes three configurable tip/tilt (TT) or tip/tilt/focus (TTF) On-Instrument Wavefront Sensors (OIWFS). These sensors are positioned over natural guide star (NGS) asterisms using movable polar-coordinate pick-off arms (POA) that patrol an approximately 2-arcminute circular field-of-view (FOV). The POAs are capable of colliding with one another, so an algorithm for coordinated motion that avoids contact is required. We have adopted an approach in which arm motion is evaluated using the gradient descent of a scalar potential field that includes an attractive component towards the goal configuration (locations of target stars), and repulsive components to avoid obstacles (proximity to adjacent arms). The…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
