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Wilde, N. (author), Smith, Stephen L. (author), Alonso-Mora, J. (author)
When designing a motion planner for autonomous robots there are usually multiple objectives to be considered. However, a cost function that yields the desired trade-off between objectives is not easily obtainable. A common technique across many applications is to use a weighted sum of relevant objective functions and then carefully adapt the...
journal article 2024
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Cheng, Gang (author), Wu, S. (author), Shi, M. (author), Dong, W. (author), Zhu, H. (author), Alonso-Mora, J. (author)
Autonomous navigation of Micro Aerial Vehicles (MAVs) in dynamic and unknown environments is a complex and challenging task. Current works rely on assumptions to solve the problem. The MAV's pose is precisely known, the dynamic obstacles can be explicitly segmented from static ones, their number is known and fixed, or they can be modeled with...
journal article 2023
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Park, Shinkyu (author), Cáp, M. (author), Alonso-Mora, J. (author), Ratti, Carlo (author), Rus, Daniela (author)
In this article, we propose a trajectory planning algorithm that enables autonomous surface vessels to perform socially compliant navigation in a city's canal. The key idea behind the proposed algorithm is to adopt an optimal control formulation in which the deviation of movements of the autonomous vessel from nominal movements of human...
journal article 2021
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Ferreira de Brito, B.F. (author), Floor, Boaz (author), Ferranti, L. (author), Alonso-Mora, J. (author)
This letter presents a method for local motion planning in unstructured environments with static and moving obstacles, such as humans. Given a reference path and speed, our optimization-based receding-horizon approach computes a local trajectory that minimizes the tracking error while avoiding obstacles. We build on nonlinear model-predictive...
journal article 2019
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Zhu, H. (author), Alonso-Mora, J. (author)
Safe autonomous navigation of microair vehicles in cluttered dynamic environments is challenging due to the uncertainties arising from robot localization, sensing, and motion disturbances. This letter presents a probabilistic collision avoidance method for navigation among other robots and moving obstacles, such as humans. The approach...
journal article 2019
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