Two possible sets of planning variables for human arm movement are point angles and hand position. Although one might expect these possibilities to be mutually exclusive, recently an apparently contradictory set of data has appeared that indicated straight-line trajectories in both hand space and joint space at the same time. To assist in distinguishing between these viewpoints applied to the same data, we have theoretically characterized the set of trajectories derivable from a joint based planning strategy and have compared them to experimental measurements. We conclude that the apparent straight-lines in joint space happen to be artifacts of movement kinematics near the workspace boundary.

Gait study plays an important role in the walking robot, because it is the foundation of walking robots. The robot must first determine the walking pattern and rules, thus we can evolve further design, control, analysis or study. This research focus on hexapod and quadruped walking robots, and establishes a mathematical model which can fully describe natural and artificial gaits, and systematically plan and express them. Another point of this research is planning walk trajectory of robot. Here we purpose a new concept of foot trajectory planning, and establish S-V-A-J models for feet motion. We try to make robots move forward with constant velocity, as a goal, by using piecewise function of cam design theory. Therefore robot can walk with constant velocity and maintain the continuity of acceleration.

The thesis proposes a 3D navigation and planning system for an autonomous remotely controlled quadcopter (drone). The solution uses the drone sensor data along with the data processed from the video camera image stream, without having any knowledge of its surroundings beforehand and without using any nav- igation signal (GPS). The video camera data are transformed into a sparse point- cloud representation, from it is created an occupancy map of the surrounding area with adaptive cell size. The planner can construct trajectory plans in the map, respecting the detected obstacles. The planned trajectory is executed by a simple drone controller. The proposed system includes a simulator which enables virtual execution of the whole process. The thesis composes originally independent and incompatible sub- systems into a single compactly working system. The functionality of the system is demonstrated on a few simple scenarios, one of which is the return of the drone to its starting location.

In order for a mobile robot to complete its task it must be able to plan and follow a trajectory. Depending on the environment, it may also be necessary to follow a given velocity profile. This is known as temporal planning. Temporal planning can be used to minimize time of motion and to avoid moving obstacles. For example, assuming the mobile robot is an intelligent wheelchair, it must follow a prescribed path (sidewalk, hospital corridor) while following a strict speed limit (slowing down for pedestrians, cars). Computing a realistic velocity profile for a mobile robot is a challenging task due to a large number of kinematic and dynamic constraints that are involved. Unlike prior works which performed temporal planning in a 2-dimensional environment, this thesis presents a new temporal planning algorithm in a 3-dimensional environment. This algorithm is implemented on a wheeled mobile robot that is to be used in a healthcare setting. The path planning stage is accomplished by using cubic spline functions. A rudimentary trajectory is created by assigning an arbitrary time to each segment of the path. This trajectory is made feasible by applying a number of constraints and using a linear scaling technique. When a velocity profile is provided, a non-linear time scaling technique is used to fit the robots center linear velocity to the specified velocity. A method for avoiding moving obstacles is also implemented. Both simulation and experimental results for the wheeled mobile robot are presented. These results show good agreement with each other. For both simulation and experimentation, six different examples of paths in the Engineering Building of the University of Saskatchewan, were used. Experiments were performed using the PowerBot mobile robot in the robotics lab at the University of Saskatchewan.

In order for a mobile robot to complete its task it must be able to plan and follow a trajectory. Depending on the environment, it may also be necessary to follow a given velocity profile. This is known as temporal planning. Temporal planning can be used to minimize time of motion and to avoid moving obstacles. For example, assuming the mobile robot is an intelligent wheelchair, it must follow a prescribed path (sidewalk, hospital corridor) while following a strict speed limit (slowing down for pedestrians, cars). Computing a realistic velocity profile for a mobile robot is a challenging task due to a large number of kinematic and dynamic constraints that are involved. Unlike prior works which performed temporal planning in a 2-dimensional environment, this thesis presents a new temporal planning algorithm in a 3-dimensional environment. This algorithm is implemented on a wheeled mobile robot that is to be used in a healthcare setting. The path planning stage is accomplished by using cubic spline functions. A rudimentary trajectory is created by assigning an arbitrary time to each segment of the path. This trajectory is made feasible by applying a number of constraints and using a linear scaling technique. When a velocity profile is provided, a non-linear time scaling technique is used to fit the robots center linear velocity to the specified velocity. A method for avoiding moving obstacles is also implemented. Both simulation and experimental results for the wheeled mobile robot are presented. These results show good agreement with each other. For both simulation and experimentation, six different examples of paths in the Engineering Building of the University of Saskatchewan, were used. Experiments were performed using the PowerBot mobile robot in the robotics lab at the University of Saskatchewan.

The diploma thesis deals with a new approach to create a robotic arm trajectory. The first part descibes existing methods of trajectory planning. The second part shows virtual point method, implementation of the trajectory planning into the web environment and trajectory generation. Third part descibes the virtual robot model and designed comunnication protocols. The fourth part shows grafical user interface and his posibilities. The last part presents implemention of web aplication into industrial visualization.

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Trajectory planning is an important component of autonomous driving. It takes the result of route-level navigation plan and generates the motion-level commands that steer an autonomous passenger vehicle (APV). Prior work on solving this problem uses either a sampling-based or optimization-based trajectory planner, accompanied by some high-level rule generation components.

In this thesis, we consider the trajectory planning of an autonomous vehicle to cross an intersection within a given time interval. The vehicle communicates its sensordata to a central coordinator which then computes the trajectory for the given time horizon and sends it back to the vehicle. We consider a realistic scenario in which the communication links are unreliable, the evolution of the state has noise (e.g., due to the model simplification and environmental disturbances), and the observationis noisy (e.g., due to noisy sensing and/or delayed information). The intersection crossing is modeled as a chance constraint problem and the stochastic noise evolution is restricted by a terminal constraint. The communication impairments are modeled as packet drop probabilities and Kalman estimation techniques are used for predicting the states in the presence of state and observation noises. A robust sub-optimalsolution is obtained using convex optimization methods which ensures that the intersection is crossed by the vehicle in the given time interval with very low chance of failure.

Cada vez mais empilhadeiras robóticas são utilizadas para a tarefa de transporte em indústrias e armazéns. O gerenciamento dessas empilhadeiras é a chave para um sistema de transporte eficiente visando maximizar sua taxa de transferência. Um dos principais problemas na operação desses sistemas é a decisão de roteamento das empilhadeiras dentro dos depósitos. Este trabalho propõe um algoritmo de roteamento com a capacidade de realizar a otimização das rotas em tempo-real. Na computação da rota são considerados o desvio de obstáculos, as dimensões e as propriedades físicas das empilhadeiras, pois uma trajetória calculada deste ponto de referência está livre de colisões durante a execução do roteamento. Para realizar os testes foram utilizados os softwares Player/Stage, os quais permitem que simulações do funcionamento do sistema de roteamento sejam realizadas antes que os algoritmos sejam testados em robôs reais. Através dos testes simulados, analisou-se a capacidade de locomoção das empilhadeiras referente ao calculo da melhor rota no ambiente proposto, com o intuito de melhorar o ganho de performance no planejamento de trajetória. / Forklift robots have been increasingly used in transport tasks in industries and warehouses. The key to an efficient transport system is held by a sound management of these forklifts that aim to maximize the transference rate. One of the main problems faced by the transportation systems is routing decision for forklifts within warehouse. The present paper proposes a routing algorithm to calculate optimal routes in real time. Therefore, its computation takes into account obstacle avoidance, the dimension and physical properties of the forklifts, since the calculated path regarding the routing is conflict-free. Simulations were carried out using the software Player/Stage before the algorithms were tested in a real robot. Simulated tests were analyzed in order to observe the locomotion ability of forklifts regarding calculation of the best route in the environment proposed to improve the trajectory planning performance will be assessed.