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Detalhes

Detalhes

  • Nome

    João Pedro Pires
  • Cargo

    Assistente de Investigação
  • Desde

    11 abril 2023
001
Publicações

2023

Safety Standards for Collision Avoidance Systems in Agricultural Robots - A Review

Autores
Martins, JJ; Silva, M; Santos, F;

Publicação
ROBOT2022: FIFTH IBERIAN ROBOTICS CONFERENCE: ADVANCES IN ROBOTICS, VOL 1

Abstract
To produce more food and tackle the labor scarcity, agriculture needs safer robots for repetitive and unsafe tasks (such as spraying). The interaction between humans and robots presents some challenges to ensure a certifiable safe collaboration between human-robot, a reliable system that does not damage goods and plants, in a context where the environment is mostly dynamic, due to the constant environment changes. A well-known solution to this problem is the implementation of real-time collision avoidance systems. This paper presents a global overview about state of the art methods implemented in the agricultural environment that ensure human-robot collaboration according to recognised industry standards. To complement are addressed the gaps and possible specifications that need to be clarified in future standards, taking into consideration the human-machine safety requirements for agricultural autonomous mobile robots.

2023

Autonomous UAV Landing Approach for Marine Operations

Autores
Moura, A; Antunes, J; Martins, JJ; Dias, A; Martins, A; Almeida, JM; Silva, E;

Publicação
OCEANS 2023 - LIMERICK

Abstract
The use of autonomous vehicles in maritime operations is a technological challenge. In the particular case of autonomous aerial vehicles (UAVs), their application ranges from inspection and surveillance of offshore power plants, and marine life observation, to search and rescue missions. Manually landing UAVs onboard water vessels can be very challenging due to limited space onboard and wave agitation. This paper proposes an autonomous solution for the task of landing commercial multicopter UAVs with onboard cameras on water vessels, based on the detection of a custom landing platform with computer vision techniques. The autonomous landing behavior was tested in real conditions, using a research vessel at sea, where the UAV was able to detect, locate, and safely land on top of the developed landing platform.