1,363 research outputs found
Robotic Harvesting of Fruiting Vegetables: A Simulation Approach in V-REP, ROS and MATLAB
In modern agriculture, there is a high demand to move from tedious manual harvesting to a continuously automated operation. This chapter reports on designing a simulation and control platform in V-REP, ROS, and MATLAB for experimenting with sensors and manipulators in robotic harvesting of sweet pepper. The objective was to provide a completely simulated environment for improvement of visual servoing task through easy testing and debugging of control algorithms with zero damage risk to the real robot and to the actual equipment. A simulated workspace, including an exact replica of different robot manipulators, sensing mechanisms, and sweet pepper plant, and fruit system was created in V-REP. Image moment method visual servoing with eye-in-hand configuration was implemented in MATLAB, and was tested on four robotic platforms including Fanuc LR Mate 200iD, NOVABOT, multiple linear actuators, and multiple SCARA arms. Data from simulation experiments were used as inputs of the control algorithm in MATLAB, whose outputs were sent back to the simulated workspace and to the actual robots. ROS was used for exchanging data between the simulated environment and the real workspace via its publish-and-subscribe architecture. Results provided a framework for experimenting with different sensing and acting scenarios, and verified the performance functionality of the simulator
Human Following in Mobile Platforms with Person Re-Identification
Human following is a crucial feature of human-robot interaction, yet it poses
numerous challenges to mobile agents in real-world scenarios. Some major
hurdles are that the target person may be in a crowd, obstructed by others, or
facing away from the agent. To tackle these challenges, we present a novel
person re-identification module composed of three parts: a 360-degree visual
registration, a neural-based person re-identification using human faces and
torsos, and a motion tracker that records and predicts the target person's
future position. Our human-following system also addresses other challenges,
including identifying fast-moving targets with low latency, searching for
targets that move out of the camera's sight, collision avoidance, and
adaptively choosing different following mechanisms based on the distance
between the target person and the mobile agent. Extensive experiments show that
our proposed person re-identification module significantly enhances the
human-following feature compared to other baseline variants
Underwater Vehicles
For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties
Unifying Foundation Models with Quadrotor Control for Visual Tracking Beyond Object Categories
Visual control enables quadrotors to adaptively navigate using real-time
sensory data, bridging perception with action. Yet, challenges persist,
including generalization across scenarios, maintaining reliability, and
ensuring real-time responsiveness. This paper introduces a perception framework
grounded in foundation models for universal object detection and tracking,
moving beyond specific training categories. Integral to our approach is a
multi-layered tracker integrated with the foundation detector, ensuring
continuous target visibility, even when faced with motion blur, abrupt light
shifts, and occlusions. Complementing this, we introduce a model-free
controller tailored for resilient quadrotor visual tracking. Our system
operates efficiently on limited hardware, relying solely on an onboard camera
and an inertial measurement unit. Through extensive validation in diverse
challenging indoor and outdoor environments, we demonstrate our system's
effectiveness and adaptability. In conclusion, our research represents a step
forward in quadrotor visual tracking, moving from task-specific methods to more
versatile and adaptable operations
- …