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Related Concept Videos

Machines01:19

Machines

Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
Machines: Problem Solving I01:22

Machines: Problem Solving I

A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
Machines: Problem Solving II01:30

Machines: Problem Solving II

Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
Multimachine Stability01:25

Multimachine Stability

Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Parallel Processing01:20

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...

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A Versatile Approach to Polygonal Object Avoidance in Indoor Environments with Hardware Schemes Using an FPGA-Based

Mudasar Basha1,2, Munuswamy Siva Kumar1, Mangali Chinna Chinnaiah2,3

  • 1Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Green Fields, Guntur 522502, Andhra Pradesh, India.

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Summary
This summary is machine-generated.

This study introduces a novel bio-inspired flocking algorithm for multi-robot obstacle avoidance in indoor settings. The system uses distributed intelligence and hardware acceleration for efficient navigation and rendezvous behaviors.

Keywords:
behavioral controlcollision avoidancemulti-robotobject orientation

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Engineering

Background:

  • Service robots require robust obstacle avoidance for indoor navigation.
  • Existing multi-robot systems often lack efficient, bio-inspired navigation strategies.

Purpose of the Study:

  • To develop and validate a flock-type, multi-robot system for indoor obstacle avoidance.
  • To integrate distributed intelligence, behavioral control, and hardware acceleration for enhanced navigation.

Main Methods:

  • A three-stage, bio-inspired flocking algorithm was developed, incorporating polygonal obstacle estimation and the Bug2 algorithm.
  • Verilog HDL was used to design VLSI architectures for the multi-robot obstacle avoidance algorithms.
  • A novel integration of behavioral control and hardware-based partial reconfiguration (PR) flow was implemented.

Main Results:

  • The developed algorithm successfully enabled multi-robots to perform obstacle avoidance in indoor environments.
  • Experiments validated the system's effectiveness using Field-Programmable Gate Arrays (FPGA)-based multi-robots.
  • The integration of behavioral control and hardware scheme achieved efficient navigation.

Conclusions:

  • The proposed flock-type multi-robot system offers an effective solution for indoor obstacle avoidance.
  • The bio-inspired approach combined with hardware acceleration provides a scalable and efficient navigation strategy.
  • This research contributes to the advancement of autonomous service robots.