Intelligent assistive systems can navigate blind people, but most of them could only give non-intuitive cues or inefficient guidance. Based on computer vision and vibrotactile encoding, this paper presents an interactive system that provides blind people with intuitive spatial cognition. Different from the traditional auditory feedback strategy based on speech cues, this paper firstly introduces a vibration-encoded feedback method that leverages the haptic neural pathway and enables the users to interact with objects other than manipulating an assistance device. Based on this strategy, a wearable visual module based on an RGB-D camera is adopted for 3D spatial object localization, which contributes to accurate perception and quick object localization in the real environment. The experimental results on target blind individuals indicate that vibrotactile feedback reduces the task completion time by over 25% compared with the mainstream voice prompt feedback scheme. The proposed object localization system provides a more intuitive spatial navigation and comfortable wearability for blindness assistance.
ABSTRACT Huffman coding is foundational to data compression algorithms. We propose an advanced application‐specific integrated circuit (ASIC) design for a canonical Huffman encoder, optimised for high throughput and low power consumption. Our design introduces a high‐speed sorting circuit, an efficient Huffman tree canonisation algorithm and an innovative entropy‐based compressibility prediction mechanism. Implemented using 12 nm CMOS technology, the proposed solution achieves a remarkable throughput of 4 GB/s and sub‐microsecond latency for 4 KB pages, outperforming existing x86 software implementations by nearly two orders of magnitude and surpassing state‐of‐the‐art hardware accelerators. This advancement significantly enhances data processing capabilities in computational storage drives (CSDs), providing a scalable and energy‐efficient data compression solution for modern data centres.
This paper proposes a new path planning strategy - the Rapid Visible Tree (RVT) algorithm to guide a robot to its goal in a complex environment without dangerous collisions. By fusing the visibility information with the classic tree-based searching method, RVT only takes the noisy points locally acquired from the environment as input and computes the visible region at each location to decide the growing direction of the path tree. Compared with traditional methods, RVT is more efficient, lightweight, and robust. We demonstrate that the RVT algorithm can not only complete the path planning task in real-time but also explore the unknown environment in simulated or real scenes.
This paper described a spring roll-style retractable sampling arm with open cylindrical shell structure. It has small shrink volume, long expand path, low power consumption, large pushing force, and wide adaption, which can be widely used in mini-sampler in dangerous or ungetatable place to sample the rock, dust and other materials. Specifically, the design of the sampling arm is described, and finite element method is then carried out to study the relationship between geometric parameters and the largest pushing force. Finally, a simple and efficient mathematical formula on the maximum pushing force is given and it agrees well with the finite element analysis through the comparison between them. Experimental results show the feasibility of this design.
Designing small-scale, high-torque magnetorheological (MR) actuators remains a challenge, with the main difficulty being how to maximize the effective shear area within tightly constrained volumes. To address this, a novel shared-flux dual multi-drum topology is proposed and investigated, in which an electromagnetic coil activates the MR fluid regions on both sides to form eight drum-type shear gaps, thereby improving the torque-to-volume ratio (TVR) and torque-to-mass ratio (TMR). This paper advances the dual multi-drum topology via figures-of-merit modeling, parametric evaluation, and experimental characterization. Analytical models for braking torque, volume, mass, and power consumption are derived to establish design-oriented relations and performance envelopes. The influence of drum length, a critical design parameter in the proposed topology, is comprehensively evaluated via finite element analysis, thereby guiding the design trade-offs. An optimized dual multi-drum MR actuator (DMDMRA) prototype (Ø31.8×46 mm, 215.6 g) was fabricated. It achieved a peak torque of 1368.48 mN·m and an off-state torque of only 9.12 mN·m, yielding a TVR of 37.48 kN/m² and a TMR of 6.35 N·m/kg. These results highlight its notable TVR and TMR advantages over other MR actuators of comparable size and further demonstrate the feasibility of the proposed topology.
Telerobot system plays an important role in executing task under hazard environment. As the computer networks such as the Internet are being used as the communication channel of telerobot systems, varying time delay causes the overall system unstable and reduces the performance of transparency. In this paper, we propose twelve operation modes with different control schemes for telerobot on the Internet with time delay. And an optimal operation mode with control scheme is specified for telerobot with time delay, based on the tradeoff between passivity and transparency properties. We experimentally confirm the validity of the proposed optimal mode and control scheme by using a simple one DOF master-slave manipulator system.
To solve the problem of autonomous obstacle avoidance in unmanned underwater vehicle (UUV) trajectory tracking, the model predictive control algorithm is applied to design obstacle avoidance controller from the point of view of trajectory re-planning. Deal with the reference target position, the obstacle information and the actual state information of the underwater vehicle, the obstacle avoidance controller plans a local reference trajectory which can avoid the obstacles. Based on the study of kinematics control, the trajectory tracking and obstacle avoidance control at the dynamic level is further expanded. Focusing on the modeling uncertainty and current disturbance in underwater environment, a model prediction and sliding mode cascaded control algorithm for UUV trajectory tracking is proposed. Considering about the constraint ability of model predictive control and the robustness of sliding mode control algorithm, the controller can realize robust trajectory tracking and obstacle avoidance control of underwater vehicle. The simulation results show that the proposed algorithm can effectively solve the speed jump and thruster saturation problem, and realize the smooth and stable trajectory tracking and obstacle avoidance control.
