This work presents the kinematic and dynamic modeling of a human–wheelchair system which considers that its center of mass is not located in the middle of the wheel’s axle. Furthermore, a novel motion controller is presented for a human–wheelchair system, which is capable of performing positioning and path-following tasks in human-shared environments. This controller design is based on two cascaded subsystems: a kinematic controller, and a dynamic controller that compensates the dynamics of the human–wheelchair system. Additionally, an algorithm based on fuzzy-logic is proposed and incorporated in the aforementioned path-following control for pedestrian collision avoidance. This methodology considers to quantify heuristics social rules to make a balance between modulating velocity or direction during the avoidance. Three different interference cases, commonly found during walking events, are tested in a structured scenario. The experimental results demonstrate that the system is capable of overcoming many usual interference situations with human obstacles. A good performance of the path-following control is also verified.

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Currently, Chile and Argentina experience serious challenges that affect their agricultural productivity. For example, in Chile, the loss of farmable field due to recent earthquakes, and volcanic eruptions as well as the loss of water reserves due to climate changes are affecting the agriculture. Additionally, both countries are facing a same problem: the loss of human labor force. Field workers are migrating from the farm to other fields in the industry which offer them more stable and more profitable jobs (like the mining industry in Chile, or car assembling lines in Argentina). In this adverse scenario, it becomes necessary to introduce and develop agricultural automation and sensing technologies for both primary (harvesting, seeding, fertilizing, spraying) and secondary tasks (grove supervision, weed detection, hauling, mowing). However, fully robotized farms are not yet a possibility since the transition from human labor force dependent farming to autonomous farming needs to be smooth and requires legal regulation not yet in discussion. In this paper, we summarize the state of the art in human-robot interaction in farmable fields, with emphasis in the current constrains associated with flexible automatization of farms in Argentina and Chile. In particular, we introduce the guidelines for designing a humanrobot interaction strategy for harvesting tasks, that could be used for other agricultural tasks.

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