Inter-row Robot Navigation using 1D Ranging Sensors

In this paper a fuzzy logic navigation controller for an inter-row agricultural robot is developed and evaluated in laboratory settings. The controller receives input from one-dimensional (1D) ranging sensors on the robotic platform, and operated on ten fuzzy rules for basic row-following behavior. The control system was implemented on basic hardware for proof of concept and operated on a commonly available microcontroller development platform and open source software libraries. The robot platform used for experimentation was a small tracked vehicle with differential steering control. Fuzzy inferencing and defuzzification, step response and cross track error were obtained from the test conducted to characterize the transient and steady state response of the controller. Controller settling times were within 4 seconds. Steady state centering errors for smooth barrier navigation were found to be within 3.5% of center for 61 cm wide solid barrier tests, and within 38% for simulated 61 cm corn row tests

Using a collaborative robot to the upper limb rehabilitation

Rehabilitation is a relevant process for the recovery from dysfunctions and improves the realization of patient's Activities of Daily Living (ADLs). Robotic systems are considered an important field within the development of physical rehabilitation, thus allowing the collection of several data, besides performing exercises with intensity and repeatedly. This paper addresses the use of a collaborative robot applied in the rehabilitation field to help the physiotherapy of upper limb of patients, specifically shoulder. To perform the movements with any patient the system must learn to behave to each of them. In this sense, the Reinforcement Learning (RL) algorithm makes the system robust and independent of the path of motion. To test this approach, it is proposed a simulation with a UR3 robot implemented in V-REP platform. The main control variable is the resistance force that the robot is able to do against the movement performed by the human arm.info:eu-repo/semantics/publishedVersio

Embedded control system for autarep - a novel autonomous articulated robotic educational platform

This research introduces an open-source framework, AUTonomous Articulated Robotic Educational Platform (AUTAREP). The platform is centred on a 6 Degree Of Freedom (DOF) arm with multiple feedbacks to ensure precision and autonomy. The sensory system consists of vision, position and force feedbacks while the actuation system comprises six precise DC servo motors. In particular, this paper presents the design of an embedded controller for AUTAREP. The proposed design of the control hardware and software interface has been tailored as per academic requirements of relevant undergraduate and postgraduate courses. Low level commands have been provided to permit readily development of applications for trainees. Advanced users can further exploit the open-source architecture of the platform. The performance of the proposed control system has been demonstrated by various experiments on the fabricated hardware. The control has been subjected to various test inputs to analyse its transient and steady state behaviour. The robot has been tested to achieve a set-point position successfully and the encoder data corresponding to all the joints has been recorded. Finally, a common application of "pick and place" has been implemented. The proposed platform is potentially beneficial in teaching engineering courses, training in industrial sector and research of advanced algorithms

Systems overview of Ono: a DIY reproducible open source social robot

One of the major obstacles in the study of HRI (human-robot interaction) with social robots is the lack of multiple identical robots that allow testing with large user groups. Often, the price of these robots prohibits using more than a handful. A lot of the commercial robots do not possess all the necessary features to perform specific HRI experiments and due to the closed nature of the platform, large modifications are nearly impossible. While open source social robots do exist, they often use high-end components and expensive manufacturing techniques, making them unsuitable for easy reproduction. To address this problem, a new social robotics platform, named Ono, was developed. The design is based on the DIY mindset of the maker movement, using off-the-shelf components and more accessible rapid prototyping and manufacturing techniques. The modular structure of the robot makes it easy to adapt to the needs of the experiment and by embracing the open source mentality, the robot can be easily reproduced or further developed by a community of users. The low cost, open nature and DIY friendliness of the robot make it an ideal candidate for HRI studies that require a large user group