Shah, Suril Vijaykumar

Remotely operated robotic systems have gained importance in executing tasks in complex and challenging environments which are difficult to automate. This paper focuses on developing reference hardware and software architectures for haptic-based teleoperation under various physical and network conditions. The system consists of a 6-DOF haptic device as the leader and a 6-DOF robotic manipulator as the follower. The control architecture used for teleoperation is Jacobian inverse control, which enables the follower to follow the leader when commanded. The performance of the proposed architecture is determined in terms of the error between current and commanded motion for different input velocities, communication delays in different network configurations, and the stable haptic force feedback at the haptic end.

The capability of smooth trajectory tracking is essential for Unmanned Aerial Vehicles (UAVs) to perform several complex tasks. This paper proposes a collision-free framework for smooth trajectory tracking of rotary wing UAVs in the presence of any external disturbances in motion of the vehicle. For this, a simplified kinematic model is used which closely resembles the behaviour of rotary wing UAVs. A Model Predictive Control (MPC) framework together with on-demand collision avoidance constraints is proposed which penalizes rapid change in subsequent control inputs, thereby enabling trajectory tracking with minimum jerk, while also avoiding collision with any obstacle in the environment. Moreover, an Asynchronous Path Smoothing (APS) strategy is concatenated with the MPC framework to deal with the external disturbances in motion of the vehicle. Numerical simulations are presented to validate the efficacy of the proposed framework.

Accurate information of inertial parameters is critical to motion planning and control of space robots. Before the launch, only a rudimentary estimate of the inertial parameters is available from experiments and CAD models. After the launch, on-orbit operations substantially alter the value of inertial parameters. In this work, a new momentum model-based method is proposed for identifying the minimal parameters of a space robot while on orbit. Minimal parameters are combinations of the inertial parameters of the links and uniquely define the momentum and dynamic models. Consequently, they are sufficient for motion planning and control of both the satellite and robotic arms mounted on it. The key to the proposed framework is the unique formulation of the momentum model in the linear form of minimal parameters. Further, to estimate the minimal parameters, a novel joint trajectory planning and optimization technique based on direction combinations of joints' velocity are proposed. The efficacy of the identification framework is demonstrated on a 12-degree-of-freedom, spatial, dual-arm space robot. The methodology is developed for tree-type space robots, requires just the pose and twist data, and is scalable with increasing number of joints.

Unmanned aerial vehicles (UAVs) have became appreciably compact and lightweight over the years, imposing stricter geometric and stability constraints. The new-generation UAVs are required to carry numerous sensors and peripheral components for a variety of tasks. These components are placed in accordance with the requirements for use and stability conditions, which complicates the determination of an optimal layout configuration. This article presents the design automation framework for determining favourable sensor placement locations under specific stability constraints. The proposed methodology is a unique end-to-end framework that determines convenient locations for sensor placement, considering the finite element model of UAVs and payload-related parameters as inputs. The design automation routine proposes an integrated approach using the support vector machine and extended pattern search algorithms to identify the design space and relevant cost function. The efficacy of the proposed framework is examined by leveraging finite element solvers to optimize payload placements on a simulated UAV model.

The increased satellite launches have made the capture of debris and On-Orbit servicing of the orbiting satellites essential. In space, objects exhibit a tumbling motion around their major inertial axis. In this paper, we propose a featureless approach for a robotic system to visual servo control in case of an uncooperative tumbling object. In contrast to the previously studied approaches that require a 3D CAD model of the object or its reconstruction, we propose a novel solution that also forgoes the need for special markers. For this purpose, we leverage a deep convolutional neural network technique to automatically estimate the axis of rotation vector of a tumbling object from its video and motion characteristics. Position-Based Visual Servoing algorithm can then use the extracted data for control. The effectiveness of the proposed framework is exhibited by implementing simulation in V-Rep on the Reachy Robotic arm.

Autonomous on-orbit servicing, such as capture, refuel, repair and refurbishment of on-orbit satellites using a robotic arm mounted on servicing satellite is one of the important components of future's space missions. Space robots increase reliability, safety, and ease of execution of space operations, but pose a novel challenge due to micro-gravity and space environments. While capturing high speed orbiting objects, robotic arms undergo impact and require appropriate modeling of the system. In this paper, a unified framework is provided for modeling impact dynamics, post-capture stabilization and target maneuvering of a multi-arm robotic system mounted on a servicing satellite while capturing orbiting objects. The dynamic model of multi-arm space robot is obtained using the Decoupled Natural Orthogonal Complement (DeNOC) based formulation and closed-loop constraint equations. All three phases of the capturing operation, namely, approach, impact, and post-impact are modeled using Impulse-momentum approach and conservation of momentum. In the approach phase, robot arms are planned to move from its initial configuration to the desired capture configuration. In the impact phase, a framework is developed to estimate the impulse forces and changes in the generalized velocities caused by the impact. In post-impact phase, these velocities are used as initial conditions for the post-impact dynamics simulations. The uncontrolled dynamics during post-impact will result in an undesirable motion, thus post-impact reactionless control (minimum base disturbance) strategy is used to maneuver the space robot's arms and target object. As such, the robotic arms can be used to maneuver an astronaut for repair of satellite. Most of the times the parameters of target object are not known. Hence, an adaptive reactionless control strategy has been devised for capturing object with unknown parameters. The effectiveness of the framework is shown using a dual-arm robot mounted on a servicing satellite performing capturing operation for multiple objects. The effects of relative velocity and angle of approach on the impact forces are also investigated.

A study presents a method that can be used to capture the target at the specified time while avoiding algorithmic as well as Jacobian singularities for a system that starts from rest. This method can alternatively be used to find a suitable initial configuration for a given desired motion state. It defines initial configuration for a given desired motion state, and the motion state of the robot as the position and velocity of a point on the base along with the joint positions and velocities of the arms. It allows additional constraints such as limits on angles, acceleration, and jerk to be satisfied while avoiding collisions.

This paper presents a novel design of a rehabilitation device for patients suffering from jaw opening impairment due to temporomandibular joint (TMJ) disorder and oral fibrosis-inducing conditions.The design of the device is posed as a mechanism synthesis problem through path generation.The path generation is formulated as a multi-objective optimisation to minimise the error between the desired and actual jaw motion profiles and maximise the mechanical advantage.An iterative solution is proposed that follows the ideal jaw profile.A systematic selection of design variables is made, followed by formulating the objective function and identifying appropriate constraints.The optimisation routine uses the steepest descent gradient to find the feasible direction for the objective function and Lagrange multipliers for imposing constraint conditions.Limits on link lengths and coordinates of optimised linkages are imposed based on ergonomic considerations.The paper presents two solutions to achieve the desired objectives: a dual fourbar mechanism covering fourteen precision points and a single fourbar mechanism covering eight precision points.The designed mechanisms are compared for accuracy, and structural analysis is carried out to assess the strength.The solution consisting of a single 4-bar mechanism is found better from the strength and manufacturability point of view.A set of human trials would be required to examine the efficacy of the proposed design.

In this paper, a kinematic motion planning algorithm for cooperative spatial payload manipulation is presented. A hierarchical approach is introduced to compute realtime collision-free motion plans for a formation of mobile manipulator robots. Initially, collision-free configurations of a deformable 2-D virtual bounding box are identified, over a planning horizon, to determine a convex workspace for the entire system. Then, 3-D payload configurations whose projections lie within the convex workspace are computed. Finally, a convex decentralized model-predictive controller is formulated to plan collision-free trajectories for the formation of mobile manipulators. Our work facilitates real-time motion planning for the system and is scalable in the number of robots. The algorithm is validated in simulated dynamic environments.

In this paper, an attempt has been made to develop a framework for closed-loop impact modeling of a multi-arm robotic system mounted on a servicing satellite while capturing a tumbling orbiting object. When the satellite is in broken state or does not have provision for grapple and tumbling, the interception is very difficult. In such cases, interception using multi-arm robotic system can be appealing as this will certainly increase the probability of grasp in comparison to a single-arm robot. When multiple arms of a robot will capture only one target object from different points of contact, then it is termed as closed-loop impact. In this paper, first, the dynamic models of a multi-arm robot and a tumbling orbiting object are obtained. The target dynamics has been modeled considering it to be a rigid body. Then, the three phases of the capturing operation, namely, approach, impact, and postimpact have been modeled. Efficacy of the framework is shown using a dual-arm robot mounted on a servicing satellite performing capturing operation when both arms of robot capture a single target object. The effects of relative velocity and angle of approach on the impact forces would also be investigated.