Deferred-Decision Trajectory Optimization
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915144755314688 |
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| author | Elango, Purnanand Sarsilmaz, Selahattin Burak Acikmese, Behcet |
| author_facet | Elango, Purnanand Sarsilmaz, Selahattin Burak Acikmese, Behcet |
| contents | We present DDTO--deferred-decision trajectory optimization--a framework for trajectory generation with resilience to unmodeled uncertainties and contingencies. The key idea is to ensure that a collection of candidate targets is reachable for as long as possible while satisfying constraints, which provides time to quantify the uncertainties. We propose optimization-based constrained reachability formulations and construct equivalent cardinality minimization problems, which then inform the design of computationally tractable and efficient solution methods that leverage state-of-the-art convex solvers and sequential convex programming (SCP) algorithms. The goal of establishing the equivalence between constrained reachability and cardinality minimization is to provide theoretically-sound underpinnings for the proposed solution methods. We demonstrate the solution methods on real-world optimal control applications encountered in quadrotor motion planning. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_06623 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Deferred-Decision Trajectory Optimization Elango, Purnanand Sarsilmaz, Selahattin Burak Acikmese, Behcet Optimization and Control We present DDTO--deferred-decision trajectory optimization--a framework for trajectory generation with resilience to unmodeled uncertainties and contingencies. The key idea is to ensure that a collection of candidate targets is reachable for as long as possible while satisfying constraints, which provides time to quantify the uncertainties. We propose optimization-based constrained reachability formulations and construct equivalent cardinality minimization problems, which then inform the design of computationally tractable and efficient solution methods that leverage state-of-the-art convex solvers and sequential convex programming (SCP) algorithms. The goal of establishing the equivalence between constrained reachability and cardinality minimization is to provide theoretically-sound underpinnings for the proposed solution methods. We demonstrate the solution methods on real-world optimal control applications encountered in quadrotor motion planning. |
| title | Deferred-Decision Trajectory Optimization |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2502.06623 |