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The navigation of autonomous vehicles around pedestrians is a key challenge when driving in urban environments. It is essential to test the proposed navigation system using simulation before moving to real-life implementation and testing. Evaluating the performance of the system requires the design of a diverse set of tests which spans the targeted working scenarios and conditions. These tests can then undergo a process of evaluation using a set of adapted performance metrics. This work addresses the problem of performance evaluation for an autonomous vehicle in a shared space with pedestrians. The methodology for designing the test simulations is discussed. Moreover, a group of performance metrics is proposed to evaluate the different aspects of the navigation: the motion safety, the quality of the generated trajectory and the comfort of the pedestrians surrounding the vehicle. Furthermore, the success/fail criterion for each metric is discussed. The implementation of the proposed evaluation method is illustrated by evaluating the performance of a pre-designed proactive navigation system using a shared space crowd simulator under Robot Operating System (ROS).

This paper presents a new flying robot, composed of two quadrotors linked by a rigid articulated passive chain. The robot obtained is similar to a parallel robot where the classic actuators have been replaced by flying drones. With its rigid structure presenting an internal degree of freedom, the robot presented is a step forward in flying robotics and presents new challenges for the design of its feedback control. In this paper the dynamic modelling of the robot is analyzed. From this analysis, a decoupling property is extracted leading to a cascaded controller based on feedback linearization. An application to trajectory tracking is developed. The effectiveness and robustness against noise in pose estimation of the proposed controller is verified through a realistic simulation.

Typically, for pick-and-place robots operating at high speeds, an enormous amount of energy is lost during the robot braking phase. This is due to the fact that, during such operational phase, most of the energy is dissipated as heat on the braking resistances of the motor drivers. To increase the energy efficiency during the high-speed pick-and-place cycles, this article investigates the use of variable stiffness springs (VSS) in parallel configuration with the motors. These springs store the energy during the braking phase, instead of dissipating it. The energy is then released to actuate the robot in a next displacement phase. This design approach is combined with a motion generator which seeks to optimize trajectories for input torques reduction (and thus of energy consumption), through solving a boundary value problem (BVP) based on the robot dynamics. Experimental results of the suggested approach on a five-bar mechanism show the drastic reduction of input torques and therefore of energetic losses.

Among region-based descriptors, geometric moments have been widely exploited to design visual servoing schemes. However, they present several disadvantages such as high sensitivity to noise measurement, high dynamic range and information redundancy (since they are not computed onto orthogonal basis). In this paper, we propose to use a class of orthogonal moments (namely Legendre moments) instead of geometric moments to improve the behavior of moment-based control schemes. The descriptive form of the interaction matrix related to the Legendre moments computed from a set of points is rst derived. Six visual features are then selected to design a partially-decoupled control scheme. Finally simulated and experimental results are presented to illustrate the validity of our proposal.

Reactive navigation in very cluttered environment while insuring maximum safety and task efficiency is a challenging subject. This paper proposes online and adaptive elliptic trajectories to perform smooth and safe mobile robot navigation. These trajectories use limit-cycle principle already applied in the literature but with the difference that the applied limit-cycles are now elliptic (not circular) and are more generic and flexible to perform navigation in environments with different kinds of obstacles shape. The set points given to the robot are generated while following reactive obstacle avoidance algorithm embedded in a multi-controller architecture (Obstacle avoidanceand Attraction to the targetcontrollers). This algorithm uses specific reference frame which gives accurate indication of robot situation. The robot knows thus if it must avoid the obstacle in clockwise or counter-clockwise direction and prevent robot from local minima, dead ends and oscillations. The stability of the proposed bottom-up control architecture is proved according to Lyapunov synthesis. Simulations and experiments in different environments are performed to demonstrate the efficiency and the reliability of the proposed control architecture.

Abstract: Robot inverse kinematics based on Jacobian inversion encounters critical issues of kinematic singularities. In this paper, several techniques based on damped least squares are proposed to lead robot pass through kinematic singularities without excessive joint velocities. Unlike other work in which the same damping factor is used for all singular vectors, this paper proposes a different damping coefficient for each singular vector based on corresponding singular value of the Jacobian. Moreover, a continuous distribution of damping factor following Gaussian function guarantees the continuous in joint velocities. A genetic algorithm is utilized to search for the best maximum damping factor and singular region, which used to require ad hoc searching in other works. As a result, end effector tracking error, which is inherited from damped least squares by introducing damping factors, is minimized. The effectiveness of our approach is compared with other methods in both non-redundant robot and redundant robot.

A major problem in the design of control laws dedicated to mobile robots appears when the classical hypothesis of rolling without sliding wheels is violated. It is generally the case for off-road vehicles as adherence conditions are often not satisfactory and sliding can then cease to be negligible. Consequently theoretical performance is impaired and the vehicle is no longer accurately controlled.

When designing an accurate automated guidance system for vehicles, a major problem is sliding and pseudo-sliding effects. This is especially the case in agricultural applications, where five-centimetre accuracy with respect to the desired trajectory is required, although the vehicles are moving on slippery ground. It has been established that RTK GPS was a very suitable sensor to achieve automated guidance with such high precision: several control laws have been designed for vehicles equipped with this sensor, and provide the expected guidance accuracy as long as the vehicles do not slide. In previous work, further control developments have been proposed to take sliding into account: guidance accuracy in slippery environments has been shown to be preserved, except transiently at the beginning/end of curves. In this paper, the design of this control law is first recalled and discussed. A Model Predictive Control method is then applied in order to preserve accuracy of guidance even during these curvature transitions. Finally, the overall control scheme is implemented, and improvements with respect to previous guidance laws are demonstrated through full-scale experiments.

Automatic guidance of urban electric vehicles is addressed in this paper. It is shown that nonlinear control design (namely chained form conversion) and the use of a RTK GPS sensor allow to achieve curved path following with a very high accuracy. Extensive experiments, carried out with a Cycab vehicle, are discussed.

Precision agriculture involves very accurate farm vehicle control along recorded paths. Such repetitive tasks could be handled using Automatic Guided Vehicles (AGV). In this paper, we address the problem of farm tractor control using a single CP-DGPS receiver. A non linear, velocity independent control law has been designed to perform both curved paths and straight lines following. It relies upon the kinematic model of the farm tractor. The control law has been implemented on a commercial farm tractor. Step response as well as curve following are presented and discussed.

We have been interested in Automatic Guided Vehicles (AGV) for several years. In this paper, we synthesize controllers for AGV applications. Particularly, we are interested in road following and direction change tasks, and in analyzing the influence of roll and pitch perturbations on vehicle behaviour. We use the bicycle as the kinematic vehicle model, and we choose the white band position of the road as the sensor signal. We define an interaction between the camera, which is mounted inside the vehicle, and the white band detected in the image space. Using this kind of interaction, we present how to use a pole assignment technique to solve the servoing task. We show the simulation and experimental resul ts (1/10 scale demonstrator) with and without perturbations. Then, we investigate in robust controller to slow down the effect of perturbations on the vehicle behaviour.

We have been interested in Automatic Guided Vehicles (AGV) for several years. In this paper, we synthesize controllers for AGV applications. Particularly, we are interested in road following and direction change tasks, and in analyzing the influence of roll and pitch perturbations on vehicle behaviour. We use the bicycle as the kinematic vehicle model, and we choose the white band position of the road as the sensor signal. We define an interaction between the camera, which is mounted inside the vehicle, and the white band detected in the image space. Using this kind of interaction, we present how to use a pole assignment technique to solve the servoing task. We show the simulation and experimental results (1/10 scale demonstrator) with and without perturbations.

This article investigates the feasibility of replacing metal robot links by wooden bodies for eco-sustainable design’s purpose. Wood is a material with low environmental impact and a good mass-to-stiffness ratio. However, it has significant dimensional and mechanical variabilities. This is an issue for industrial robots that must be accurate and stiff. To guarantee stiffness and accuracy performance of a wooden robot, we propose an integrated design process combining (i) proper wood selection, (ii) adequate sensor-based control strategies to ensure robot accuracy, and (iii) a robust design approach dealing with wood uncertainties. Based on the use of this integrated design process, a prototype of a wooden five-bar mechanism is designed and manufactured. Experimental results show that it is realistic to design a wooden robot with performance compatible with industry requirements in terms of stiffness (deformations lower than 400 μm for 20 N loads) and accuracy (repeatability lower than 60 μm), guaranteed in a workspace of 800 mm × 200 mm. This study provides a first step toward the eco-sustainable mechanical design of robots.

Parallel robots present singular configurations that divide the operational workspace into several aspects. It was proven that type 2 and leg passive joint twist system (LPJTS) singularities can be crossed with a trajectory respecting a given dynamic criterion. However, the practical implementation of a controller able to track such trajectories is up to now limited to restrictive cases of type 2 singularities crossing. Analyzing the structure of the inverse dynamic model, this paper proposes a global solution allowing the tracking of trajectories respecting the general criterion for any singularity that leads to potential issues of dynamic model degeneracy. The tracking is operated in the robot joint space. Experimental results on a five-bar mechanism showed the controller ability to successfully cross type 2 singularities.