Max Robotics — Global Service Robot Directory + US Certification

About

Tankut Acarman is a prominent researcher specializing in autonomous systems, trajectory planning, and multi-vehicle coordination, with a particular focus on solving complex optimization problems for real-world robotics applications. His work has made significant contributions to the field of cooperative motion planning for nonholonomic robots operating in constrained and cluttered environments — a challenge critical to advancing autonomous driving and indoor robotic navigation. Acarman's most influential work, "Optimal Cooperative Maneuver Planning for Multiple Nonholonomic Robots in a Tiny Environment via Adaptive-Scaling Constrained Optimization" (2021, 65 citations), introduced novel adaptive-scaling techniques to address the inherent non-convexity and computational complexity of multi-vehicle trajectory planning. His subsequent research expanded on safety guarantees in optimization-based planners, notably through the "Embodied Footprints" framework (2023, 34 citations), which addresses collision-avoidance violations between trajectory collocation points — a subtle but safety-critical gap in autonomous driving systems. His benchmarking study (2022, 25 citations) further established methodological standards for evaluating cooperative planning algorithms in unstructured environments. With a growing citation record and research addressing both theoretical rigor and practical deployment, Acarman's work is essential reading for anyone pursuing autonomous navigation, motion planning, or multi-agent robotics.