With the rapid development of computer vision, vision-based simultaneous localization and mapping (vSLAM) plays an increasingly important role in the field of unmanned driving. However, traditional SLAM methods based on a monocular camera only perform well in simple indoor environments or urban environments with obvious structural features. In off-road environments, the situation that SLAM encounters

The goal of this research is to develop a “Selective Grasp” system with which robots can grasp and identify the target object even in occluded environments. In pursuit of this goal, we first develop a robot hand on which proximity sensors are mounted all around. In addition to the development, we propose a sensor model of the robot hand. By using the sensor model, robots can estimate the distance to

The hydrodynamic model can be used to predict velocity of underwater vehicles in still water. However, there are few economical and effective methods for estimating the hydrodynamic parameters of irregular-shaped underwater vehicles. Thus, this paper proposes a hybrid estimation strategy, which contains a rough estimation using a least squares (LS) based algorithm and a precise estimation using an

In recent years, we have witnessed the proliferation of so-called collaborative robots or cobots, that are designed to work safely along with human operators. These cobots typically use the “program from demonstration” paradigm to record and replay trajectories, rather than the traditional source-code based programming approach. While this requires less knowledge from the operator, the basic functionality

We investigate Model Predictive Control (MPC) schemes without stabilizing constraints or costs for the set-point stabilization of holonomic mobile robots. Herein, we ensure closed-loop asymptotic stability using the concept of cost controllability. To this end, we derive a growth bound on the finite-horizon value function in terms of the running costs evaluated at the current state, which is then used

This work presents a series of demonstrations of our self-reconfigurable modular robots (SRMR) “Roombots” in the context of adaptive and assistive furniture. In literature, simulations are often ahead of what currently can be demonstrated in hardware with such systems due to significant challenges in transferring them to the real world. Here, we describe how Roombots tackled these difficulties in real

Despite the increment of researches related to Social Assistive Robotics (SAR), achieving a plausible Robot-Assisted Diagnosis (RAD) for Children with Autism Spectrum Disorders (CwASD) remains a considerable challenge to the clinical and robotics community. The work of specialists regarding ASD diagnosis is hard and labor-intensive due to the condition’s manifestations are inherently heterogeneous

Recent research on automotive driving has developed an efficient end-to-end learning mode that directly maps visual input to control commands. However, it models distinct driving variations in a single network, which increases learning complexity and is less adaptive for modular integration. In this paper, we re-investigate human’s driving style and propose to learn an intermediate driving intention

Most designs of wearable robots are based on human biomechanical statistics, engineering experience or individual experiments. Despite great successes, few of them consider the human–robot integration and individual differences between users. Additionally, the design periods, cost and safety also need to be further improved. Learning from the natural driving mechanism of human body, we propose a general

A 3UPU-I parallel sensor with six division-force limbs and six standard force sensors is developed for measuring robotic wrist load. Its measuring approach and performances are studied and evaluated. A prototype of the developed parallel sensor is built up and its merits are analyzed. A statics equation among the forces of the six standard force sensors and the wrist load is established, and a mapped

This work details the design and simulation results of a bioinspired minimalist algorithm based on C. elegans, using autonomous agents to forage for attractant energy sources. The robotic agents are energy-constrained and depend on the energy they forage to recharge their batteries, which is significant as the foraging task is one of the canonical testbeds for cooperative robotics. The algorithm consists

Intelligent vehicle is an inevitable trend in urban transportation development. Whether for driver assistance systems or advanced driverless systems, safety issues are one of the cores of these systems. This paper proposes a scene safety evaluation method based on binocular camera. By proposing a comprehensive safety evaluation model, the uncertainty of the scene can be represented with a single value

Wall-climbing robots have been widely applied in the inspection of smooth walls. However, only a few adhesion methods have been developed for robots that will allow them to climb cliffs and dusty, high-altitude, rough walls (constructed using coarse concrete, bricks, and stones, etc.) that may be subjected to vibrations. This paper proposes a suitable adhesion method that employs grappling-hook-like

In this article, we show how visual constraints such as homographies and fundamental matrices can be integrated tightly into the locomotion controller of a humanoid robot to drive it from one configuration to another (pose-regulation), only by means of images. The visual errors generated by these constraints are stacked as terms of the objective function of a Quadratic Program so as to specify the

Legged-wheeled robots combine the advantages of efficient wheeled mobility with the capability of adapting to real-world terrains through the legged locomotion. Thanks to their hybrid mobility skill, they can excel in many application scenarios where other mobile platforms are not suitable for. However, the improved versatility of their mobility increases the number of constraints in their motion control

With a focus on a number of state-of-the-art techniques in the area of autonomous non-rigid space systems control, realization of a comprehensive strategy is worthy of investigation to handle a set of parameters of the present overactuated processes with model uncertainties. In a word, the subject behind the research is to guarantee the desirable performance of a class of the autonomous space systems

Miniaturized grippers that possess an untethered structure are suitable for a wide range of tasks, ranging from micromanipulation and microassembly to minimally invasive surgical interventions. In order to robustly perform such tasks, it is critical to properly estimate their overall configuration. Previous studies on tracking and control of miniaturized agents estimated mainly their 2D pixel position

This paper introduces a real-time path optimization and control strategy for shape memory alloy (SMA) actuated cardiac ablation catheters, potentially enabling the creation of more precise lesions with reduced procedure times and improved patient outcomes. Catheter tip locations and orientations are optimized using parallel genetic algorithms to produce continuous ablation paths with near normal tissue

We describe how a robot can develop knowledge of the objects in its environment directly from unsupervised sensorimotor experience. The object knowledge consists of multiple integrated representations: trackers that form spatio-temporal clusters of sensory experience, percepts that represent properties for the tracked objects, classes that support efficient generalization from past experience, and

A human's ability to perform physical tasks is limited by physical strength, not by intelligence. We define "extenders" as a class of robot manipulators worn by humans to augment human mechanical strength, while the wearer's intellect remains the central control system for manipulating the extender. Our research objective is to determine the ground rules for the design and control of robotic systems