Model predictive control of connected spacecraft formation.

In this contribution the authors discuss the application of Model Predictive Control (MPC) to achieve a connected network formation of spacecrafts. A set of three spacecrafts are used to achieve in-plane formation which are initially in a connected network. Two scenarios including formation control and formation control with collision avoidance in a leader-follower configuration is addressed through simulation studies. The aspect of MPC stability and network connectivity is also addressed briefly in the context of formation control

Tracking and estimation of surgical tool pose based on the vision system for surgical robot.

The aim of this research is to customise a surgical robot. This research presents a Virtual Dynamic Tri-crossbar and a Virtual Stable Graph (VDT-VSG) which simplifies the task of tracing the needle angle and location

Implementation and validation of an event-based real-time nonlinear model predictive control framework with ROS interface for single and multi-robot systems.

This paper presents the implementation and experimental validation of a central control framework. The presented framework addresses the need for a controller, which provides high performance combined with a low-computational load while being on-line adaptable to changes in the control scenario. Examples for such scenarios are cooperative control, task-based control and fault-tolerant control, where the system's topology, dynamics, objectives and constraints are changing. The framework combines a fast Nonlinear Model Predictive Control (NMPC), a communication interface with the Robot Operating System (ROS) as well as a modularization that allows an event-based change of the NMPC scenario. To experimentally validate performance and event-based adaptability of the framework, this paper is using a cooperative control scenario of Unmanned Aerial Vehicles (UAVs)

Detecting and tracking the position of suspicious objects using vision system.

Vision-based object tracking is crucial for both civil and military applications. A range of hazards to cyber safety, vital infrastructure, and public privacy are posed by the rise of drones, or unmanned aerial vehicles (UAV). As a result, identifying suspicious drones/UAV is a serious issue that has attracted attention recently. The key focus of this research is to develop a unique virtual coloured marker based tracking algorithm to recognise and predict the pose of a detected object within the camera field-of-view. After detecting the object, proposed method begins by determining the area of detected object as reference-contour. Following that, a Virtual-Bounding Box (V-BB) is developed over the reference-contour by meeting the minimum area of contour criteria. In order to track and estimate the precise location of the detected object in two-dimensions during observations, a Virtual Dynamic Crossline with a Virtual Static Graph (VDC-VSG) was constructed to follow the motion of V-BB, which is considered as a virtual coloured marker. Additionally, the virtual coloured marker helps to avoid issues linked to ambient lighting and chromatic variation. To some extent, it can function efficiently during obstructions like rapid position fluctuations, low resolution and noises etc. The efficacy of the developed algorithm is evaluated by testing with significant number of aerial sequences, including benchmark footage and the outputs were outstanding, with better results. The suggested method will support future industry of computer vision-based intelligent systems. Potential applications of the proposed method includes object detection and analysis applied to the field of security and defence

Model predictive cooperative localization control of multiple UAVs using potential function sensor constraints: a workflow to create sensor constraint based potential functions for the control of cooperative localization scenarios with mobile robots.

The global localization of multiple mobile robots can be achieved cost efficiently by localizing one robot globally and the others in relation to it using local sensor data. However, the drawback of this cooperative localization is the requirement of continuous sensor information. Due to a limited sensor perception space, the tracking task to continuously maintain this sensor information is challenging. To address this problem, this contribution is presenting a model predictive control (MPC) approach for such cooperative localization scenarios. In particular, the present work shows a novel workflow to describe sensor limitations with the help of potential functions. In addition, a compact motion model for multi-rotor drones is introduced to achieve MPC real-time capability. The effectiveness of the presented approach is demonstrated in a numerical simulation, an experimental indoor scenario with two quadrotors as well as multiple indoor scenarios of a quadrotor obstacle evasion maneuver

Vision based relative position estimation in surgical robotics.

Teleoperation-based Robotic-Assisted Minimally In-vasive Surgery (RAMIS) has gained immense popularity in medical field. However, limited physical interaction between the surgeon and patient poses a significant challenge. In RAMIS, the surgeon operates the robotic system remotely, which can diminish the personal connection and raise concerns about immediate responsiveness to unforeseen situations. Additionally, patients may perceive RAMIS as riskier due to potential technological failures and a lack of direct surgeon control. Surgeons have identified accidental clashes between surgical instruments and tissues as a critical issue. This work presents a technique that measures the distance between a surgical tool and tissue by extracting feature points from a Static Virtual Marker (SVM) and employing a classic feature detection algorithm Fast Oriented and Rotated Brief (ORB). Using a customized surgical robot and a ROS-based transform measurement system, this approach was successfully validated in the Gazebo simulation environment, offering safer surgical operations

Tracking and estimation of surgical instrument position and angle in surgical robot using vision system.

A da Vinci robot endoscopic-camera gives surgeons a magnified 2D view of the operating area, but additional time is required to detect and estimate the location of the surgical-instrument during an operation. The main focus and novelty of this research is to develop a new virtual coloured marker-based tracking algorithm for estimating the posture and orientation of the instrument. Initially, the developed algorithm begins by determining the coloured area of the instrument as reference-contour. Followed by a new Virtual-Rotating Bounding Rectangle (V-RBR) created over the reference-contour by meeting the minimum area of contour criteria. Additionally, a new Virtual Dynamic Multi-line Crossbar and a Virtual Static Graph (VDMC-VSG) was constructed to trace the movement of V-RBR, which helps to estimate the pose and angle of the targeted instrument in 2D during observations. V-RBR is considered as virtual coloured marker, it avoids ambient illumination-related difficulties. The proposed approach performed excellently in Gazebo-simulation and the overall accuracy is 91.3 % obtained by comparing with Robot Operating System (ROS)-based Transform measuring system, which uses robot kinematics

Modeling and Control of Aerial Manipulation Vehicle with Visual sensor

Modeling and control of a Quadrotor with robotic arm which uses vision sensor is discussed. A quadrotor model coupled with a two link manipulator is first developed and then the integrated control mechanism is investigated. An Image Based Visual Servo system is introduced and then used with the aerial manipulator to successfully perform specific tasks of positioning and stabilization during manipulation

Operational space control of a lightweight robotic arm actuated by shape memory alloy wires: a comparative study.

This article presents the design and control of a two-link lightweight robotic arm using shape memory alloy wires as actuators. Both a single-wire actuated system and an antagonistic configuration system are tested in open and closed loops. The mathematical model of the shape memory alloy wire, as well as the kinematics and dynamics of the robotic arm, are presented. The operational space control of the robotic arm is performed using a joint space control in the inner loop and closed-loop inverse kinematics in the outer loop. In order to choose the best joint space control approach, a comparative study of four different control approaches (proportional derivative, sliding mode, adaptive, and adaptive sliding mode control) is carried out for the proposed model. From this comparative analysis, the adaptive controller was chosen to perform operational space control. This control helps us to perform accurate positioning of the end-effector of shape memory alloy wire–based robotic arm. The complete operational space control was successfully tested through simulation studies performing position reference tracking in the end-effector space. Through simulation studies, the proposed control solution is successfully verified to control the hysteretic robotic arm

Cooperative localization of unmanned aerial vehicles in ROS - The Atlas node

This paper is presenting the implementation and experimental validation of the cooperative robot localization framework “Atlas”. For ease of application, Atlas is implemented as a package for the Robot Operating System (ROS). ATLAS is based on dynamic cooperative sensor fusion which optimizes the estimated pose with respect to noise, respective variance. This paper validates the applicability of Atlas by cooperatively localizing multiple real quadrotors using cameras and fiduciary markers