This paper proposes and evaluates swarming mechanisms of patrolling unmanned aerial vehicles (UAVs) that can collectively search a region for intruding UAVs. The main contributions include the development of multi-objective searching strategies and investigation of the required sensor configurations for the patrolling UAVs. Numerical results reveal that it is sometimes better to search through a region with a single swarm rather than multiple swarms deployed over sub-regions. Moreover, a large communication range does not necessarily improve search performances, and the patrolling swarm must have a speed close to the speed of the intruding UAVs to maximize the search performances.

This paper presents an attractive position-based visual servoing approach for camera-in-hand robotic systerns. The major contribution of this work is in devising an elegant and pragmatic approach for 3D visual tracking, which yielded good target tracking performance. It differs from the other known techniques, in its approach for image interpretation and the introduction of a Smith-like predictor control structure to overcome the inherent multi-rate time delayed nature of the visual servoing system. A complete description is made of the proposed MSP-DH visual servoing system. Experiments on the target tracking performance on XY planar motion using an AdeptOne robotic system are presented to illustrate the controller performance. In addition, experimental results have clearly shown the capability of the MSP-DH visual servoing system in performing 3D-dynamic visual servoing.

In Part 1 of this paper we have investigated numerically the quasiperiodic and frequency locked solutions of mathematical model of a robot with one degree of freedom. In this paper we extend our investigations to the region of transient chaos. The zones of chaotic transients are very broad and lie beyond the parameter range of engineering significance. Transiently chaotic zones exhibit a complex structure, fractally intertwined with tongues of regular pattern and cover a broad range of control parameter L. The crisis point for the onset of sustained chaos lies extremely far from the point of onset of transient chaos.

Traditionally, robot motion planners use Voronoi Diagrams for generating admissible paths that connect an initial with a final configuration. When dynamic scenarios are involved, these techniques imply a heavy computational cost. The novelty of the technique presented here is that it can provide fast and particularly suitable routes without considering the full scenario if environmental changes appear. The new method is designed to work with a post-process technique in order to provide admissible paths for car-like robots coping with kinematic constraints. This new approach is capable of supplying continuous paths and also elaborate maneuvers if cluttered environments are involved.

For acquiring a broad view in an unknown environment, we proposed a control strategy based on the Bézier curve for the snake robot raising its head. Then, an improved discretization method was developed to accommodate the backbone curves with more complex shapes. Besides, in order to determine the condition of using the improved discretization method, energy of framed space curve is introduced originally to estimate the shape complexity of the backbone curve. At last, based on degree elevation of the Bézier curve, an obstacle avoidance strategy of the head-raising motion was proposed and validated through simulation.

The motion planner presented in this paper enables the user to design movements in an interactive way, and to integrate sensor signals efficiently. In addition to the usual movements bound to a path, which can now be combined like lego pieces, smooth and fast reactions to arbitrary changes of the target are also provided. This motion planner opens new possibilities for flexible and sensor-oriented robotics, as examples from its implementation on two robots show.

In this paper fhe problem of motion control of a biped is considered. We develop a new method based on multi-agent associated Neural AIGLS (On-line Augmented Integration of Gradient and Last Sguare method) – RSPN (Recursive Stochastic Petri Nets) strategy. This method deals with organization and coordination aspects in an intelligent modeling of human motion. We propose a cooperative multi-agent model. Based on this model, we develop a control kernel named IMCOK (Intelligent Motion COntrol Kernel) which consists of a controller, a coordinator and an executor of different cycles of the motion of the biped. When walking, IMCOK receives messages and sends offers. A Decision Making of Actions (DMA) is developed at the supervisor level. The articulator agents partially planify the motion of the associated non-articulator agents. The system is hybrid and distributed functionally. The learning of the biped is performed using an On-line Augmented Integration of Gradient and Last Sguare Neural Networks based algorithm. In the conflictual situations of sending or receiving messages by the managers of MABS we apply a new strategy: Recursive Stochastic Petri Nets (RSPN). This module is fundamental in the On-line information processing between agents. It allows particularly the Recursive strategy concept. Cognitive agents communicate with reactive (non-articulator) agents in order to generate the motion.

Tangential motion on a finger pad is a promising method of transmitting directional tactile information to human users. This study examined the identification and discrimination of tangential force motion on an index finger pad. An experimental device was built to automatically and randomly move a small probe in eight radial directions (45° apart) and two distances (0.5 and 1.5 mm). Index fingers of 62 subjects were tested. The results showed that moving the probe at 1.5 mm was detected with more accuracy than the 0.5 mm one. And, the absolute direction was not a statistically significant variable affecting accuracy for 1.5 mm distance, but was a significant effect for 0.5 mm distance. Implications of these results are discussed and future developments are offered within the context of a proposed Braille design with tangential actuators.

This paper introduces an intuitive and safe command approach for a quadrotor, where inertial and muscular gestures are used for semi-autonomous flight. A bracelet composed of gyroscopes, accelerometers, and electromyographic sensors is used to detect user gestures, then an algorithm is proposed to interpret the signals as flight commands. The main goal is to provide a wearable, easy-to-handle human–machine interface for users a to safely command this kind of vehicles, even for inexpert operators. Safety measures are incorporated in the scheme to further enhance the user’s experience. Experimental tests are performed to validate the proposal.

A global optimal control algorithm was developed with the aim of finding a control which satisfies some special requirements in the sense of obtaining singular position free movement of the redundant robot mechanism. The solution of the developed global optimal control algorithm is a boundary value problem. The additional constraints in the boundary value problem were constructed with the use of an optimization process. The usefulness of the developed global optimal control algorithm is demonstrated by the example of the 3 DOFs planar redundant robot mechanism of SCARA type.

The problem of constructing a smooth path with respect to time through N given points in configuration space is considered. Two variants of an algorithm suggested by Paul are presented and evaluated. It is shown that the algorithms suggested in this paper yield in general considerable improvements in two respects: Firstly, the deviation of the resulting path from the given points is reduced markedly and secondly, the overall time needed for the movement is reduced significantly and consequently, is closer to the true minimum-time. The price to be paid for these improvements is a moderate increase of computation time allowing still online use of the algorithm.

Collective decision-making by a swarm of robots is of paramount importance. In particular, the problem of collective perception wherein a swarm of robots aims to achieve consensus on the prevalent feature in the environment. Recently, this problem has been formulated as a discrete collective estimation scenario to estimate their proportion rather than deciding about the prevalent one. Nevertheless, the performance of the existing strategies to resolve this scenario is either poor or depends on higher communication bandwidth. In this work, we propose a novel decision-making strategy based on maximum likelihood estimate sharing (MLES) to resolve the discrete collective estimation scenario. Experimentally, we compare the tradeoff speed versus accuracy of MLES with state-of-the-art methods in the literature, such as direct comparison (DC) and distributed Bayesian belief sharing (DBBS). Interestingly, MLES achieves an accurate consensus nearly 20% faster than DBBS, its communication bandwidth requirement is the same as DC but six times less than DBBS, and its computational complexity is $O(1)$. Furthermore, we investigate how noisy sensors affect the effectiveness of the strategies under consideration, with MLES showing better sustainability.

This study presents a novel 4-DOF two-limb gripper mechanism with a simple design that offers high adaptability for different objects. The mechanism integrates a three-finger end effector and employs a 2-DOF driving system in both serial kinematic chains mounted on the base, addressing performance problems caused by moving actuators. First, the architecture of the gripper mechanism is described, and its mobility is verified. Next, the inverse and forward kinematic problems are solved, and the Jacobian matrix is derived to analyze the singularity conditions. The inverse and forward singularity surfaces are plotted. The workspace is investigated using a search method, and two indices, manipulability and dexterity, are studied. The proposed manipulator’s parameters are optimized for improved dexterity. The novel gripper mechanism has high potential for grasping different types of parts within a large workspace, making it a valuable addition to the field of robotics.

This paper develops the conceptual design and error analysis of a cable-driven parallel robot (CDPR). The earlier error analysis of CDPRs generally regarded the cable around the pulley as a center point and neglected the radius of the pulleys. In this paper, the conceptual design of a CDPR with pulleys on its base platform is performed, and an error mapping model considering the influence of radius of the pulleys for the CDPR is established through kinematics analysis and a full matrix complete differential method. Monte Carlo simulation is adopted to deal with the sensitivity analysis, which can directly describe the contribution of each error component to the total orientation error of the CDPR by virtue of the error modeling. The results show that the sensitivity coefficients of pulleys’ geometric errors and geometric errors of the cables are relatively larger, which confirms that the cable length errors and pulleys’ geometric errors should be given higher priority in design and processing.

Deformable linear objects (DLOs) have a wide variety of applications in a range of fields. Their key characteristic is that they extend much further in one of their dimensions than in the other two. Accurate motion planning is particularly important in the case of DLOs used in robotics applications. In this paper, a new strategy for planning the motions of DLOs under multiple constraints is proposed. The DLO was modeled as Cosserat elastic rods so that the deformation is simulated accurately and efficiently. The control of the motion of the DLO was enhanced by supplementing one gripper installed at each end with additional supports. This allows DLOs to undergo complex deformations, and thus avoid collisions during motion. The appropriate number of supports and their positions were determined, and then a rapidly exploring random tree algorithm was used to search for the best path to guide the DLO toward its target destination. The motion of the simulated DLO is described as it is controlled using two grippers and specific numbers of supports. To prove that the proposed DLO motion planning strategy can successfully guide relatively long DLOs through complex environments without colliding with obstacles, a case study of the strategy was conducted when guiding a DLO through a puzzle.

A new type of 28-DOF (degree of freedom) full-size humanoid robot, driven by a closed-chain type of joint actuation system, is developed in this paper. Each leg of the robot is composed of six joints, where three are at the hip, one is at the knee, and two are at the ankle. The robot has six joints for each arm, one balancing joint, and three joints for the head, with two cameras. The weight of the robot is 75 kg, and its height is 168 cm.

The actuation systems of the pitching joint for the arms and legs of the robot are designed based on a closed-chain mechanism composed of four bar links driven by a ball screw, and each leg of the robot is designed to support 95 kg weight to include a 20 kg payload that can be carried by the robot arms having very light designs (with weight 8.5 kg), but each capable of carrying a 10 kg payload.

An analysis of the closed-chain joint actuation systems of a light arm capable of handling heavy objects is performed, and the light arm is designed via finite-element method analysis performed using ANSYS. In addition, the kinematic analysis and the detailed structure of the arm and leg of the robot are performed.

The main controller uses the ARM processor and a distributed controller for the leg joints is developed using the TMS320c2407 processor with the communications between the main and joint controllers being performed via the CAN system.

Good performances of the proposed robot is demonstrated by presenting several experimental results; these include (1) experimentally handling a 13 kg payload, (2) through walking experiments of the robot supporting a 85 kg load, and (3) measurements of the arm and leg joint motors while performing walking experiments.

This paper describes the design and experimental validation of an omnidirectional unmanned ground vehicle built for operation on real-world, unstructured terrains. The omnidirectional capabilities of this robot give it advantages over skid-steered or Ackermann-steered vehicles in tight and confined spaces. The robot's conventional wheels allow for operation in natural, outdoor environments as compared to omnidirectional robots that use specialized wheels with small, slender rollers and parts that can easily become obstructed with debris and dirt. Additionally, the robot's active split offset caster design allows the robot to kinematically follow continuous but non-differentiable paths and heading angles regardless of its current kinematic configuration. The active split offset caster design also results in less scrubbing torque and therefore less energy consumption during steering as compared to actively steered caster designs. The focus of this paper is the robot's mechanical design as it relates to kinematic isotropy and experimental validation of the design.

In this paper, we have reported a trajectory planning for a 1-degree-of-freedom clutched robotic arm. This novel robotic arm has only one actuator, but it can work in a spatial space by using a proper clutch system and a suitable trajectory planning. An algorithm has been proposed for generating a prescribed trajectory by means of seven operation modes, which are generated by different states of clutches.

This paper presents a kinematics modeling and hybrid motion planning framework for wheeled-legged rovers. It is a unified solution for wheeled-legged rovers to traverse multiple challenging terrains using hybrid locomotion. A kinematic model is first established to describe the rover’s motions. Then, a hybrid motion planning framework is proposed to determine the rover’s gait patterns and parameterize the legs’ and the body’s trajectories. Furthermore, an optimization algorithm based on B-spline is utilized to minimize the motors’ energy dissipation and generate smooth trajectories. The wheeled and legged hybridization allows the rover for faster locomotion while maintaining high stability. Besides, it also improves the rover’s ability to overcome obstacles. Prototype experiments are carried out in more complex environments to verify the rover’s flexibility and maneuverability to traverse irregular terrains. The proposed algorithm reduces the swing amplitude by 83.3% compared to purely legged locomotion.

Ankle rehabilitation robots are widely used due to nerve injuries and sports injuries leading to decreased mobility of the ankle joint. However, the motion of most ankle rehabilitation robots has distinctions with human ankle physiological structure. In order to achieve more accurate rehabilitation training of the ankle joint, this paper proposes a novel 3-UPU parallel rehabilitation mechanism. In a certain range, the mechanism can perform rotation around any axis within the midplane, which means that the mechanism can achieve non-fixed-point rotation around the instantaneous axis of the ankle joint. The mechanism has three degrees of freedom and can perform ankle pronation/supination and inversion/eversion movements. Taking into account the structural differences of different human bodies, the rotating axis of the mechanism can be adjusted in both height and angle. Then, the workspace of the mechanism was solved, and the size parameters of the mechanism are analyzed based on the characteristics of the size parameters of the mechanism and the motion range of the ankle. A genetic algorithm was employed to optimize the mechanism’s parameters. Next, the motion trajectory of the mechanism was planned, and the length change of the mechanism driving pair during the motion planning of the angle was obtained through kinematics simulation. Finally, experimental verification of the above rehabilitation training methods indicates that the mechanism meets the requirements of ankle rehabilitation.