Obstacle avoidance control of a human-in-the-loop mobile robot system using harmonic potential fields

A multiple working mode approach to robotic hammering: Analysis and experiments

A robot arm may be in need for performing various operations, especially for service robots and space robots. This paper presents a strategy that allows a modular and reconfigurable robot to safely perform nail hammering without hardware enhancements. The purpose is to equip a versatile robot arm with hammering capability that can be used if needed. To do this, a multiple working mode approach is applied to switch the selected joint(s) to passive mode with friction compensation to allow free rotation during impact. Analytic impulse models are used to predict joint impulses and serve as criteria for mode switching. Advantages of the proposed approach include savings on space, weight, costs, and complexity for a limited range of nail/board environments. An experimental study has validated analytic models of hammering and demonstrated the effectiveness of the proposed approach.

An Approximated, Control Affine Model for a Strawberry Field Scouting Robot Considering Wheel–Terrain Interaction

Recently, autonomous field robots have been investigated as a labor-reducing means to scout through commercial strawberry fields for disease detection or fruit harvesting. To achieve accurate over-bed and cross-bed motions, it is preferred to design the motion controller based on a precise dynamic model. Here, a dynamic model is developed for a custom-designed strawberry field robot considering terramechanic wheel–terrain interaction. Different from existing models, a torus geometry is considered for the wheels. In order to obtain a control affine model, the longitudinal force is curve-fitted using a polynomial function of the slip/skid ratio, while the lateral force is curve-fitted using an exponential function of both the slip/skid ratio and slip angle. An extended Kalman filter (EKF) is then developed to estimate the unknown parameters in the approximated model such that the state variables propagated by such a model can match experimental data. The approximated model and the EKF-based parameter estimation method are then validated in a commercial strawberry farm.

A Novel Framework for Multi-Agent Systems Using a Decentralized Strategy

This work addresses a new framework that proposes a decentralized strategy for collective and collaborative behaviours of multi-agent systems. This framework includes a new clustering behaviour that causes agents in the swarm to agree on attending a group and allocating a leader for each group, in a decentralized and local manner. The leader of each group employs a vision-based goal detection algorithm to find and acquire the goal in a cluttered environment. As soon as the leader starts moving, each member is enabled to move in the same direction by staying coordinated with the leader and maintaining the desired formation pattern. In addition, an exploration algorithm is designed and integrated into the framework so as to allow each group to be able to explore goals in a collaborative and efficient manner. A series of comprehensive experiments are conducted in order to verify the overall performance of the proposed framework.

Hitchhiking Based Symbiotic Multi-Robot Navigation in Sensor Networks

Robot navigation is a complex process that involves real-time localization, obstacle avoidance, map update, control, and path planning. Thus, it is also a computationally expensive process, especially in multi-robot systems. This paper presents a cooperative multi-robot navigation scheme in which a robot can ‘hitchhike’ another robot, i.e., two robots going to the same (or close) destination navigate together in a leader–follower system assisted by visual servoing. Although such cooperative navigation has many benefits compared to traditional approaches with separate navigation, there are many constraints to implementing such a system. A sensor network removes those constraints by enabling multiple robots to communicate with each other to exchange meaningful information such as their respective positions, goal and destination locations, and drastically improves the efficiency of symbiotic multi-robot navigation through hitchhiking. We show that the proposed system enables efficient navigation of multi-robots without loss of information in a sensor network. Efficiency improvements in terms of reduced waiting time of the hitchhiker, not missing potential drivers, best driver-profile match, and velocity tuning are discussed. Novel algorithms for partial hitchhiking, and multi-driver hitchhiking are proposed. A novel case of hitchhiking based simultaneous multi-robot teleoperation by a single operation is also proposed. All the proposed algorithms are verified by experiments in both simulation and real environment.