Novel Integrated System Architecture for an Autonomous Jumping Micro-Robot

As the capability and complexity of robotic platforms continue to evolve from the macro to micro-scale, innovation of such systems is driven by the notion that a robot must be able to sense, think, and act [1]. The traditional architecture of a robotic platform consists of a structural layer upon which, actuators, controls, power, and communication modules are integrated for optimal system performance. The structural layer, for many micro-scale platforms, has commonly been implemented using a silicon die, thus leading to robotic platforms referred to as "walking chips" [2]. In this thesis, the first-ever jumping microrobotic platform is demonstrated using a hybrid integration approach to assemble on-board sensing and power directly onto a polymer chassis. The microrobot detects a change in light intensity and ignites 0.21mg of integrated nanoporous energetic silicon, resulting in 246µJ of kinetic energy and a vertical jump height of 8cm

Evolving controllers for robots with multimodal locomotion

Animals have inspired numerous studies on robot locomotion, but the problem of how autonomous robots can learn to take advantage of multimodal locomotion remains largely unexplored. In this paper, we study how a robot with two different means of locomotion can effective learn when to use each one based only on the limited information it can obtain through its onboard sensors. We conduct a series of simulation-based experiments using a task where a wheeled robot capable of jumping has to navigate to a target destination as quickly as possible in environments containing obstacles. We apply evolutionary techniques to synthesize neural controllers for the robot, and we analyze the evolved behaviors. The results show that the robot succeeds in learning when to drive and when to jump. The results also show that, compared with unimodal locomotion, multimodal locomotion allows for simpler and higher performing behaviors to evolve.info:eu-repo/semantics/acceptedVersio

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Steerable miniature jumping robot

Jumping is used in nature by many small animals to locomote in cluttered environments or in rough terrain. It offers small systems the benefit of overcoming relatively large obstacles at a low energetic cost. In order to be able to perform repetitive jumps in a given direction, it is important to be able to upright after landing, steer and jump again. In this article, we review and evaluate the uprighting and steering principles of existing jumping robots and present a novel spherical robot with a mass of 14g and a size of 18cm that can jump up to 62cm at a take-off angle of 75°, recover passively after landing, orient itself, and jump again. We describe its design details and fabrication methods, characterize its jumping performance, and demonstrate the remote controlled prototype repetitively moving over an obstacle course where it has to climb stairs and go through a window. (See videos 1-4 in the electronic supplementary material.

Advances in Bio-Inspired Robots

This book covers three major topics, specifically Biomimetic Robot Design, Mechanical System Design from Bio-Inspiration, and Bio-Inspired Analysis on A Mechanical System. The Biomimetic Robot Design part introduces research on flexible jumping robots, snake robots, and small flying robots, while the Mechanical System Design from Bio-Inspiration part introduces Bioinspired Divide-and-Conquer Design Methodology, Modular Cable-Driven Human-Like Robotic Arm andWall-Climbing Robot. Finally, in the Bio-Inspired Analysis on A Mechanical System part, research contents on the control strategy of Surgical Assistant Robot, modeling of Underwater Thruster, and optimization of Humanoid Robot are introduced

New Method for Localization and Human Being Detection using UWB Technology: Helpful Solution for Rescue Robots

International audienceTwo challenges for rescue robots are to detect human beings and to have an accurate positioning system. In indoor positioning, GPS receivers cannot be used due to the reflections or attenuation caused by obstacles. To detect human beings, sensors such as thermal camera, ultrasonic and microphone can be embedded on the rescue robot. The drawback of these sensors is the detection range. These sensors have to be in close proximity to the victim in order to detect it. UWB technology is then very helpful to ensure precise localization of the rescue robot inside the disaster site and detect human beings. We propose a new method to both detect human beings and locate the rescue robot at the same time. To achieve these goals we optimize the design of UWB pulses based on B-splines. The spectral effectiveness is optimized so the symbols are easier to detect and the mitigation with noise is reduced. Our positioning system performs to locate the rescue robot with an accuracy about 2 centimeters. During some tests we discover that UWB signal characteristics abruptly change after passing through a human body. Our system uses this particular signature to detect human body

A Review of Lower Limb Exoskeletons

In general, exoskeletons are defined as wearable robotic mechanisms for providing mobility. In the last six decades, many research work have been achieved to enhance the performance of exoskeletons thus developing them to nearly commercialized products. In this paper, a review is made for the lower limb exoskeleton concerning history, classification, selection and development, also a discussion for the most important aspects of comparison between different designs is presented. Further, some concluding remarks are withdrawn which could be useful for future work. Keywords: Exoskeletons, Lower extremity exoskeleton, Wearable robot

Sensing, Design Optimization, and Motion Planning for Agile Pneumatic Artificial Muscle-Driven Robots

Mechanical compliance in robotic systems facilitates safe human-robot interaction and improves robot adaptation to environmental uncertainty. Several promising compliant actuator technologies have emerged from the field of soft robotics, in particular the pneumatic artificial muscle—a soft, lightweight actuator that contracts under pressure. The pneumatic muscle's passive compliance eliminates the need for precise high-bandwidth actuator control to simulate mechanical impedance. However, the pneumatic muscle is limited in practical robot applications—particularly, without sacrificing robot agility—due to several key challenges: development of compatible soft sensors, translation of conventional high-level control and planning techniques to pneumatic muscle-driven systems, and limitations in pneumatic muscle pressurization rate and force generation capabilities. This work seeks to address these challenges, via a threefold approach, to access the benefits of compliant robot actuation while maximizing the robot's dynamic capabilities. The first objective targets the development of a pneumatic muscle design with integrated sensing to enable kinematic and dynamic state estimation of muscle-actuated robots without hindering muscle compliance. The second objective focuses on the construction of a trajectory optimization framework for planning dynamic robot maneuvers using 'burst-inflation' muscle pressure control. Finally, the third objective explores a design optimization strategy utilizing biological joint mechanisms to compensate for pneumatic muscle limitations and maximize robot agility.Ph.D

Using Origami Folding Techniques to Study the Effect of Non-Linear Stiffness on the Performance of Jumping Mechanism

This research uses Origami patterns and folding techniques to generate non-linear force displacement profiles and study their effect on jumping mechanisms. In this case, the jumping mechanism is comprised of two masses connected by a Tachi-Miura Polyhedron (TMP) with non-linear stiffness characteristics under tensile and compressive loads. The strain-softening behavior exhibited by the TMP enables us to optimize the design of the structure for improved jumping performance. I derive the equations of motion of the jumping process for the given mechanism and combine them with the kinematics of the TMP structure to obtain numerical solutions for the optimum design. The results correlate to given geometric configurations for the TMP that result in the two optimum objectives: The maximum time spent in the air and maximum clearance off the ground. I then physically manufacture the design and conduct compression tests to measure the force-displacement response and confirm it with the theoretical approach based on the kinematics. Experimental data from the compression tests show a hysteresis problem where the force-displacement profile exhibits different behavior whether the structure is being compressed or released. I investigate two methods to nullify the hysteresis when compressing or releasing the mechanism and then discuss their results. This research can lead to easily manufacturable jumping robotic mechanisms with improved energy storage and jumping performance. Additionally, I learn more about how to use origami techniques to harness unique stiffness properties and apply them to a variety of scenarios