Multivariate evaluation of interactive robot systems

In designing robot systems for human interaction, designers draw on aspects of human behavior that help them achieve specific design goals. For instance, the designer of an educational robot system may use speech, gaze, and gesture cues in a way that enhances its student’s learning. But what set of behaviors improve such outcomes? How might designers of such a robot system determine this set of behaviors? Conventional approaches to answering such questions primarily involve designers carrying out a series of experiments in which they manipulate a small number of design variables and measure the effects of these manipulations on specific interaction outcomes. However, these methods become infeasible when the design space is large and when the designer needs to understand the extent to which each variable contributes to achieving the desired effects. In this paper, we present a novel multivariate method for evaluating what behaviors of interactive robot systems improve interaction outcomes. We illustrate the use of this method in a case study in which we explore how different types of narrative gestures of a storytelling robot improve its users’ recall of the robot’s story, their ability to retell the robot’s story, their perceptions of and rapport with the robot, and their overall engagement in the experiment.     

Optimality and competitiveness of exploring polygons by mobile robots

A mobile robot, represented by a point moving along a polygonal line in the plane, has to explore an unknown polygon and return to the starting point. The robot has a sensing area which can be a circle or a square centered at the robot. This area shifts while the robot moves inside the polygon, and at each point of its trajectory the robot “sees” (explores) all points for which the segment between the robot and the point is contained in the polygon and in the sensing area. We focus on two tasks: exploring the entire polygon and exploring only its boundary. We consider several scenarios: both shapes of the sensing area and the Manhattan and the Euclidean metrics.We focus on two quality benchmarks for exploration performance: optimality (the length of the trajectory of the robot is equal to that of the optimal robot knowing the polygon) and competitiveness (the length of the trajectory of the robot is at most a constant multiple of that of the optimal robot knowing the polygon). Most of our results concern rectilinear polygons. We show that optimal exploration is possible in only one scenario, that of exploring the boundary by a robot with square sensing area, starting at the boundary and using the Manhattan metric. For this case we give an optimal exploration algorithm, and in all other scenarios we prove impossibility of optimal exploration. For competitiveness the situation is more optimistic: we show a competitive exploration algorithm for rectilinear polygons whenever the sensing area is a square, for both tasks, regardless of the metric and of the starting point. Finally, we show a competitive exploration algorithm for arbitrary convex polygons, for both shapes of the sensing area, regardless of the metric and of the starting point.     

Region with velocity constraints: map information and its usage for safe motion planning of a mobile robot in a public environment

Recently, various autonomous mobile robots have been developed for practical use. To support the coexistence of robots and humans in real environments, we propose a concept named ‘Region with Velocity Constraints (RVC),’ which is set around hazardous areas. RVCs are regions where the velocities of the robot are constrained to predefined values. Inside the RVCs, the robot has to reduce its translational velocity to avoid predicted hazards such as collisions with obstacles, and to reduce its rotational velocity to prevent undesirable motions such as sharp turns. We also propose a motion planning method for navigating the mobile robot in an environment with RVCs based on the Navigation Function and Global Dynamic Window Approach. Our method generates a trajectory satisfying both translational and rotational velocity constraints to be compatible with the surroundings. Moreover, to demonstrate the validity of our method, we performed numerical simulations and experiments.     

Pose estimation-based path planning for a tracked mobile robot traversing uneven terrains

A novel path-planning algorithm is proposed for a tracked mobile robot to traverse uneven terrains, which can efficiently search for stability sub-optimal paths. This algorithm consists of combining two RRT-like algorithms (the Transition-based RRT (T-RRT) and the Dynamic-Domain RRT (DD-RRT) algorithms) bidirectionally and of representing the robot–terrain interaction with the robot’s quasi-static tip-over stability measure (assuming that the robot traverses uneven terrains at low speed for safety). The robot’s stability is computed by first estimating the robot’s pose, which in turn is interpreted as a contact problem, formulated as a linear complementarity problem (LCP), and solved using the Lemke’s method (which guarantees a fast convergence). The present work compares the performance of the proposed algorithm to other RRT-like algorithms (in terms of planning time, rate of success in finding solutions and the associated cost values) over various uneven terrains and shows that the proposed algorithm can be advantageous over its counterparts in various aspects of the planning performance.     

Coupled Oscillator Control of Autonomous Mobile Robots

This paper introduces a nonlinear oscillator scheme to control autonomous mobile robots. The method is based on observations of a successful control mechanism used in nature, the Central Pattern Generator. Simulations were used to assess the performance of oscillator controller when used to implement several behaviors in an autonomous robot operating in a closed arena. A sequence of basic behaviors (random wandering, obstacle avoidance and light following) was coordinated in the robot to produce the higher behavior of foraging for light. The controller is explored in simulations and tests on physical robots. It is shown that the oscillator—based controller outperforms a reactive controller in the tasks of exploring an arena with irregular walls and in searching for light.     

Pose Planning for a Mobile Manipulator Based on Joint Motions for Posture Adjustment to End-Effector Error

This paper proposes a motion planning method for a mobile manipulator. In general, humans can grasp an object by various ways which depend on object posture, position and so on. The objective of this paper is to present how to detect the pose of a mobile manipulator under the condition that several ways of grasping are given to the robot. Motion errors and object position errors are considered to detect robot pose in our method because these affect the grasp motion of the robot hand. Coping with these errors, we will propose an effective pose searching method for a mobile manipulator from numerous pose candidates. The performance of the proposed method is illustrated by simulation and experiment.     

Positioning device for outdoor mobile robots using optical sensors and lasers

We propose a novel method for positioning a mobile robot in an outdoor environment using lasers and optical sensors. Position estimation via a noncontact optical method is useful because the information from the wheel odometer and the global positioning system in a mobile robot is unreliable in some situations. Contact optical sensors such as computer mouse are designed to be in contact with a surface and do not function well in strong ambient light conditions. To mitigate the challenges of an outdoor environment, we developed an optical device with a bandpass filter and a pipe to restrict solar light and to detect translation. The use of two devices enables sensing of the mobile robot’s position, including posture. Furthermore, employing a collimated laser beam allows measurements against a surface to be invariable with the distance to the surface. In this paper, we describe motion estimation, device configurations, and several tests for performance evaluation. We also present the experimental positioning results from a vehicle equipped with our optical device on an outdoor path. Finally, we discuss an improvement in postural accuracy by combining an optical device with precise gyroscopes.     

Iterative Path Tracking of an Omni-Directional Mobile Robot

We propose a path-tracking algorithm that is developed using an iterative learning control (ILC) technique and use the algorithm to control an omni-directional mobile robot. The proposed algorithm can be categorized as an open–closed PD-type ILC; it generates robot velocity commands by a PD-type ILC update rule using both previous and current information. When applied to the omni-directional mobile robot, it can decrease position errors and track the desired trajectory. Under the general problem setting that includes a mobile robot, we show that the proposed algorithm guarantees that the system states, outputs and control inputs converge to within small error bounds around the desired ones even under state disturbances, measurement noises and initial state errors. By using simulation and experimental tests, we demonstrate that the proposed algorithm converges fast to the desired path, and results in small root-mean-square (r.m.s.) position error under various surface conditions. The proposed algorithm shows better path-tracking performance than the conventional PID algorithm and achieves faster convergence and lower r.m.s. error than the existing two ILC algorithms.     

A new adaptive tracking control scheme of wheeled mobile robot without longitudinal velocity measurement

This paper proposes a new adaptive trajectory tracking control scheme of the wheeled mobile robot without longitudinal velocity measurement. First, based on a kinematic controller, we obtain a new tracking error equation, which is suitable to develop an adaptive controller. Then, we develop a new adaptive trajectory tracking controller, which does not need any accurate values of the wheeled mobile robot parameters, including the driving motor parameters. Moreover, as the longitudinal velocity measurement is still difficult, this controller is developed without longitudinal velocity measurement. In addition, this new adaptive controller introduces a method to improve the control performance. The stability of the closed‐loop system is presented using the direct Lyapunov method. Finally, numerous simulations verify the effectiveness of the new controller.     

时滞的非完整动力学系统滑模抗干扰跟踪控制

针对具有外部扰动和时滞的非完整轮式移动机器人系统,本文阐述了一种基于非线性扰动观测器的时滞滑模控制方法.首先,利用扰动观测器估计系统的外部扰动;然后,用极坐标转化移动机器人的姿态,并用计算转矩法对机器人的动力学方程进行反馈线性化.设计带时滞控制的滑模,目的是使移动机器人渐近稳定在期望轨迹上,并有效地减小控制增益的过高估计.最后,利用李雅普诺夫函数建立闭环系统的稳定性.仿真结果表明,该方案具有良好的跟踪精度和鲁棒性.