RELATÓRIO TÉCNICO 007/2023/COPLAN/DPAE/PU/UFSC

Dados de consumo e despesas com energia elétrica dos diversos campi e unidades da Instituição para o ano de 2022. Além disso, são apresentados o padrão de consumo das Unidades Consumidoras (UCs) e fatores que influenciaram os respectivos gastos

Relatório Técnico 07/2022/COPLAN/DPAE

Dados de consumo e despesas com energia elétrica dos diversos campi e unidades da Instituição para o ano de 2021. Além disso, são apresentados o padrão de consumo das Unidades Consumidoras (UCs) e fatores que influenciaram os respectivos gastos

A Model-Predictive Motion Planner for the IARA Autonomous Car

We present the Model-Predictive Motion Planner (MPMP) of the Intelligent Autonomous Robotic Automobile (IARA). IARA is a fully autonomous car that uses a path planner to compute a path from its current position to the desired destination. Using this path, the current position, a goal in the path and a map, IARA's MPMP is able to compute smooth trajectories from its current position to the goal in less than 50 ms. MPMP computes the poses of these trajectories so that they follow the path closely and, at the same time, are at a safe distance of eventual obstacles. Our experiments have shown that MPMP is able to compute trajectories that precisely follow a path produced by a Human driver (distance of 0.15 m in average) while smoothly driving IARA at speeds of up to 32.4 km/h (9 m/s).Comment: This is a preprint. Accepted by 2017 IEEE International Conference on Robotics and Automation (ICRA