Abstract
In recent years, there has been great interest from researchers in legged robots. These robots have unique characteristics and are suitable for complex working environments with uneven terrains and unexpected obstacles. They can work on almost any type of terrain, overcome obstacles like stairs much more efficiently than wheeled or tracked robots, and cause a lower impact on the ground when compared with other locomotion systems. To expand the application of robotics to new complex areas, it is essential to accurately locate the robot and plan safe trajectories regardless of the environment, terrain, or weather conditions. Using a legged locomotion system raises some concerns regarding the 3D localization, mapping, and trajectory planning algorithms. This paper reviews those problems and describes the current approaches to localize a robot, map an environment and plan safe trajectories for quadruped robots.

Abstract
Soil Moisture (SM) is one of the most critical factors for a crop's growth, yield, and quality. Although Ground-Penetrating RADAR (GPR) is commonly used in satelite observation to analyze soil moisture, it is not cost-effective for agricultural applications. Automotive RADAR uses the concept of Frequency-Modulated Continuous Wave (FMCW) and is more competitive in terms of price. This paper evaluates the viability of using a cost-effective RADAR as a substitute for GPR for soil moisture content estimation. The research consisted of four experiments, and the results show that the RADAR's output signal and the soil moisture sensor SEN0193 have a high correlation with values as high as 0.93 when the SM is below 15%. Such results show that the tested sensor (and its cost-effective working principle) are able to determine soil water content (with certain limitations) in a non-intrusive, proximal sensing manner.

Abstract
There has been an increase in the variety of harvesting manipulators. However, sometimes the lack of efficiency of these manipulators makes it difficult to compete with harvesting tasks performed by humans. One of the key components of these manipulators is the end-effector, responsible for picking the fruits from the plant. This paper studies different types of end-effectors used by some harvesting manipulators and compares them. The objective is to analyse their advantages and limitations to better understand the requirements to design an end-effector to improve the performance of a custom Selective Compliance Assembly Robot Arm (SCARA) on the harvest of different types of fruits.

Abstract
In Industry 4.0 and Agriculture 4.0, there are logistics areas where robots can play an important role, for example by following a person at a certain distance. These robots can transport heavy tools or simply help collect certain items, such as harvested fruits. The use of Ultra Wide Band (UWB) transceivers as range sensors is becoming very common in the field of robotics, i.e. for localising goods and machines. Since UWB technology has very accurate time resolution, it is advantageous for techniques such as Time Of Arrival (TOA), which can estimate distance by measuring the time between message frames. In this work, UWB transceivers are used as range sensors to track pedestrians/operators. In this work we propose the use of two algorithms for relative localization, between a person and robot. Both algorithms use a similar 2dimensional occupancy grid, but differ in filtering. The first is based on a Extended Kalman Filter (EKF) that fuses the range sensor with odometry. The second is based on an Histogram Filter that calculates the pedestrian position by discretizing the state space in well-defined regions. Finally, a controller is implemented to autonomously command the robot. Both approaches are tested and compared on a real differential drive robot. Both proposed solutions are able to follow a pedestrian at speeds of 0.1m/s, and are promising solutions to complement other solutions based on cameras and LiDAR.

Abstract
Robotics will play an essential role in agriculture. Deploying agricultural robots on the farm is still a challenging task due to the terrain's irregularity and size. Optimal path planning solutions may fail in larger terrains due to memory requirements as the search space increases. This work presents a novel open-source solution called AgRob Topologic Path Planner, which is capable of performing path planning operations using a hybrid map with topological and metric representations. A local A* algorithm pre-plans and saves local paths in local metric maps, saving them into the topological structure. Then, a graph-based A* performs a global search in the topological map, using the saved local paths to provide the full trajectory. Our results demonstrate that this solution could handle large maps (5 hectares) using just 0.002 % of the search space required by a previous solution.

Abstract
Purpose The motivation for robotics research in the agricultural field has sparked in consequence of the increasing world population and decreasing agricultural labor availability. This paper aims to analyze the state of the art of pruning and harvesting manipulators used in agriculture. Design/methodology/approach A research was performed on papers that corresponded to specific keywords. Ten papers were selected based on a set of attributes that made them adequate for review. Findings The pruning manipulators were used in two different scenarios: grapevines and apple trees. These manipulators showed that a light-controlled environment could reduce visual errors and that prismatic joints on the manipulator are advantageous to obtain a higher reach. The harvesting manipulators were used for three types of fruits: strawberries, tomatoes and apples. These manipulators revealed that different kinematic configurations are required for different kinds of end-effectors, as some of these tools only require movement in the horizontal axis and others are required to reach the target with a broad range of orientations. Originality/value This work serves to reduce the gap in the literature regarding agricultural manipulators and will support new developments of novel solutions related to agricultural robotic grasping and manipulation.