Formation Control of Humanoid Robots with Obstacle & Collision Avoidance Inspired by SFM

Distributed formation control of multi humanoid robot system with obstacle avoidance and collision avoidance are presented. The architecture consists of several layers, namely consensus tracking, consensus based formation control, behaviour and physical robot layers. The formation control system was simulated in MATLAB software before it was implemented to humanoid NAO Aldebaran robots. In the experimental study the visual odometry was used to track the robots’ position and their moving direction. The result of the experiment showed that the distributed formation control design was succeed in directing the robots into their planned formation, avoiding obstacles, and avoiding collisions among themselves with certain communication topology, shape of formation, obstacles’ position and their number.

AIM: to evaluate the effect of a surgical access on postoperative morbidity and oncological safety in older patients.PATIENTS AND METHODS: a multicenter retrospective study included 179 patients aged 60–74 years who underwent surgery for middle and low rectal cancer (T1-3N0-N2bM0) in 2021-2023. The patients were divided into 3 groups: the first ones underwent robotic (ROB) surgery (n = 62), the second — laparoscopic (LAP) surgery (n = 55), and the third — open (OPEN) surgery (n = 62). Parameters of pre-, intra-, and postoperative periods and histopathological findings were evaluated. Neural network modeling was used to predict anastomotic leakage (AL).RESULTS: the blood loss was 150 (100; 200) ml with OPEN versus 100 (50; 100) with ROB and LAP, the operation time was 255 (210; 300) min with ROB versus 180 (150; 240) min with LAP and 140 (120; 150) min with OPEN. In ROB and LAP groups, anastomoses were formed in 61 (98.4%) and 54 (98.2%) cases compared with 45 (72.6%) cases in the OPEN group (p = 0.00001). The splenic flexure was mobilized in 54 (98.2%) cases in the LAP group, 55 (88.7%) cases in the OPEN group, and 50 (80.7%) cases in the ROB group (p = 0.01). Conversion rates were 10.9% (6/55) and 1.6% (1/62) in LAP and ROB groups, respectively (p = 0.00001). Postoperative complications in the OPEN group occurred in 48 (77.4%) cases compared with 31 (50%) and 12 (21.8%) in ROB and LAP groups (p = 0.02). Inflammatory complications predominated in the OPEN group. Distal and lateral margins, the quality of mesorectal excision, and the number of examined and affected lymph nodes did not differ. However, the good quality of mesorectal excision prevailed in ROB and OPEN groups, where as the satisfactory quality was more common in the LAP group. The most important predictors of AL were American Society of Anesthesiologists (ASA) physical status II, neoadjuvant chemoradiotherapy, stage I and IIa cancer, end-to-end anastomosis, Charlson Comorbidity Index scores of 3–4, and surgeon’s experience (20–40 operations for rectal cancer per year). The least important predictors were the level of mesenteric vessel ligation and the access.CONCLUSIONS: the surgical access does not affect the AL rate. The histology revealed that all the 3 approaches ensure compliance with principles of oncological safety. Compared with open surgery, robotic and laparoscopic surgery result in less blood loss and faster recovery of intestinal function; however, the operation time increases.

In this paper autonomous formation control for Unmanned Aerial Vehicles (UAVs) has been discussed and a real time solution has been put forward by benefiting General Purpose Graphical Processing Units (GPGPU) accelerated potential field approach while ensuring obstacle and collision avoidance in unknown environment by using real-time sensors. GPGPU accelerated real time formation control for UAVs was designed and the basic model of the approach has been explained in our previous work (Cetin and Yilmaz 2014). As the deficiencies of the previous approach, autonomous real time collision and coordinated obstacle avoidance features in unknown environments are also handled while maintaining formation flight conditions in this work. With these features, improved autonomous formation control approach is discussed as a real time solution. The computation is performed by using Graphical Processing Units (GPUs) as parallel computation architectures by benefiting from Single Instruction Multiple Data (SIMD) type parallel algorithms. Classic binary map conversation, connected component labeling and minimum bounding box algorithms which are commonly used for image processing applications, has been evaluated for real time obstacle detection and avoidance features by developing GPGPU suitable parallel algorithms. Real-time solution has been developed by integrated these parallel algorithms with parallel Artificial Potential Field (APF) computation algorithm. Simulation results are proved that this novel autonomous improved formation control approach is successful and it would be used in real time applications like UAV formation flight missions.

Objective To compare the clinical outcomes between minimal-invasive triangular fixation with orthopedic robot and traditional open fixation method for unilateral unstable sacral fracture patients. Methods Data of 24 consecutive patients with unilateral unstable sacral fracture who were treated from August 2014 to February 2018 were retrospectively analyzed. All patients were associated with anterior ring injuries of pelvis and received magnetic resonance of nerve (MRN) preoperatively to exclude the compression of sacral nerve by bone. All patients received surgical treatment of sacral fractures with triangular fixation and the fixation of pelvic anterior ring injuries simultaneously and two groups were divided according to the different surgical methods of sacral fractures. There were 10 males and 2 females with an average age of 36.3±1.2 years in the orthopaedic robot group. According to Dennis classification, there were 4 type I and 8 type II fractures. Two patients were associated with nerve injuries (Gibbons II 1 case, III 1 case). In traditional posterior-midline open fixation group, there were 11 males and 1 female with an average age of 38.2±1.6 years. According to Dennis classification, there were 3 type I and 9 type II fractures. Three patients were associated with nerve injuries (Gibbons II 2 cases, III 1 case). The clinical data of two group patients were collected and compared statistically. T test was used to compare the operation time, intraoperative bleeding, intraoperative fluoroscopy times, Majeed function assessment which was to evaluate the patients' clinical prognosis and healing time of fracture. χ2 test was used to compare the healing rate of fracture, accuracy assessment of fixation insertion, and Mears radiological assessment which was applied to evaluate the reduction quality of fractures. The rank sum test was used to compare Gibbons score which was applied as the index of neurological deficiency recovery. The Fisher exact test was used to compare the infection rate. Results All patients were followed up continuously for an average time of 21.2±3.2 months. The average operation time of robot group was 100.3±14.5 minutes, meanwhile the open fixation group was 202.0±18.5 min. The average intraoperative bleeding of robot group was 180.0±17.4 ml, meanwhile the open fixation group was 850.0±15.2 ml. The average intraoperative fluoroscopy time of robot group was 23.3±4.5 s, meanwhile the open fixation group was 90.0±7.7 s. All fractures were healed and no loss of reduction or fail of fixation occurred in both groups. The healing time of fracture of robot group was 8.5±1.9 months, meanwhile the open fixation group was 12.8±2.4 months. The satisfaction rates of reduction which was based on Mears-Velyvis radiological criterion of both groups were 91.7%. The accuracy rate of fixation insertion of robot group was 100% meanwhile the open fixation group was 77.78%. Majeed function assessment score of robot group was 86.2±3.4, meanwhile the open fixation group was 84.2±2.7. There was no infection occurred in robot group, meanwhile 3 patients infected in open fixation group. The Gibbons score of one patient changed from II preoperative to I postoperative and one case changed from III preoperative to II postoperative in robot group, meanwhile two patients changed from II preoperative to I postoperative and one case changed from III preoperative to II postoperative in open fixation group. The healing rate of fracture, infection rate, Majeed function assessment, Mears-Velyvis radiological evaluation criterion and Gibbons score of two groups had no significant statistical difference (P >0.05), meanwhile the operation time (t=14.99), intraoperative bleeding (t=100.46), intraoperative fluoroscopy time (t=32.13), healing time of fracture (t=4.87) and accuracy rate of fixation insertion (χ2=9.00) of orthopedic robot group were better than traditional open group and had the significant difference (P< 0.05). Conclusion The minimal-invasive triangular fixation with orthopedic robot for unilateral unstable sacral fracture had the advantages of less operation time, less intraoperative bleeding and less times of fluoroscopy, more accurate of fixation insertion and less healing time of sacral fractures compared to traditional open fixation method and should be recommended as an effective and advanced choice. Key words: Sacrum; Fractures, bone; Fracture fixation, internal; Internal fixators

This paper considers a rendezvous problem, where a group of wheeled mobile robots with sensing and power constraints is tasked to meet at a common destination. Each robot is modeled in the wheel kinematic level, which is governed by the wheel actuation power constraints. The group of robots is of a leader-follower network structure, where only the leader robot is aware of the desired destination and the follower robots are driven by the leader to the common destination via local sensing of neighboring robots. To ensure the availability of inter-robot communication, the motion of robots is constrained to preserve network connectivity, enabling leader-based guidance via connected paths. In addition, the motion of robots is further constrained to avoid collisions with other robots. To achieve these objectives, a guidance function based decentralized controller is developed to control the wheel velocities of each robot, which ensures global convergence to the destination while guaranteeing the network connectivity, collision avoidance, and not violating its sensing and actuator power capabilities. The simulation results demonstrate the effectiveness of the developed controller.

This paper presents a distributed consensus formation control with collision and obstacle avoidance using fuzzy wavelet neural networks (FWNNs) for a group of networked mobile Mecanum-wheeled omnidirectional robots (MWORs) with uncertainties. The dynamic behavior of each uncertain MWOR is modeled by a reduced three-input–three-output second-order state equation with uncertainties, and the multi-MWOR system is modeled by graph theory. Using the Lyapunov stability theory and online learning the system uncertainties via FWNNs, an adaptive and distributed consensus backstepping control approach is presented to carry out formation control in the presence of uncertainties. Collision and obstacle-avoidance methods are provided to avoid any collisions among MWORs and their working environments. Five simulations are conducted to show the effectiveness and merit of the proposed method .

Formation control has become a popular research topic in recent years. A common challenge in formation control is ensuring that robots can avoid obstacles and maintain a safe distance from one another to prevent collisions while forming a formation. In this research, a distributed formation control approach for a multi-robot system (MRS) with obstacle and collision avoidance is presented. The distributed formation control architecture is based on a consensus algorithm and consists of four layers: consensus tracking, consensus-based formation control, behavior, and physical robot layers. The system was implemented and evaluated through both simulations and experiments. Humanoid robots were used as the platform for these implementations. The result of the simulations and experiments show that the distributed formation control system successfully guided the robots into desired formation while also avoiding obstacles and preventing collisions with other robots.

In this paper, a multi-agent formation control strategy with collision avoidance and obstacle avoidance in complex environments is proposed. Under a virtual leader structure, the multi-agent formation is realized through path planning and formation control. In path planning, a transitional region based on prediction horizon is used to replan reference trajectories and avoid obstacles in advance. The virtual-leader alternation strategy and feasible state searching strategy are adopted to avoid one side obstacles and crowded obstacles, respectively. Then the path planning optimization problem is formulated by mixed-integer quadratic programming (MIQP) to calculate trajectories collision-free with obstacles. In formation control, a distributed model predictive control (DMPC) algorithm is developed to form and maintain formation. In DMPC optimization problem, the non-convex obstacle avoidance constraints are replaced with deviation constraints and linear constraints to design terminal invariant set and reduce online computation burden. Under the whole formation control strategy, the tasks of obstacle avoidance and collision avoidance are both achieved and the agents maintain the formation as much as possible. Finally, the example with different obstacle situations is discussed to illustrate the effectiveness of the proposed strategy.

Multi-agent Robots Systems (MARS) can be defined as sets of autonomous robots coordinated through a communication system to achieve cooperative tasks. During the last 20 years, MARS have found a wide range of applications in terrestrial, spatial and oceanic explorations emerging as a new research area (Cao et al. (1997)). Some advantages can be obtained from the collective behavior of MARS. For instance, the kind of tasks that can be accomplished are inherently more complex than those a single robot can accomplish. Also, the system becomes more flexible and fault-tolerant (Yamaguchi (2003)). The range of applications includes toxic residues cleaning, transportation and manipulation of large objects, alertness and exploration, searching and rescue tasks and simulation of biological entities behaviors (Arai et al. (2002)). The study ofMARS extends the classical problems of single robotswith new issues likemotion coordination, task decomposition and task assignment, network communications, searching and mapping, etc. Therefore, the study of MARS encompass distributed systems, artificial intelligence, game theory, biology, ethology, economics, control theory, etc. Motion coordination is an important research area of MARS, specifically formation control (Chen & Wang (2005)). The main goal is to coordinate a group of mobile agents or robots to achieve a desired formation pattern avoiding inter-agent collisions at the same time. The formation strategies are decentralized because it is assumed that every agent measures the position of a certain subset of agents and, eventually, it detects the position of other agents when a minimal allowed distance is violated and collision danger appears. Thus, the main intention is to achieve desired global behaviors through local interactions (Francis et al. (2004)). Also, the decentralized approaches offer greater autonomy for the robots, less computational load in control implementations and its applicability to large scale groups (Do (2007)). According to Desai (2002); Muhammad & Egerstedt (2004), the possible inter-agent communications and the desired relative position of every agent with respect to the others can be represented by a FormationGraph (FG). The application of different FG’s to the same group of robots produces different dynamics on the team behavior. In the literature, some special FG topologies are chosen and the convergence to the desired formation and non-collision is analyzed for any number of robots. A decentralized formation strategy must comply with two fundamental requirements: Global convergence to the desired formation and inter-agent collision avoidance (Cao et al. (1997)). 6

Understanding the principles involved in visually-based coordinated motor control is one of the most fundamental and most intriguing research problems across a number of areas, including psychology, neuroscience, computer vision and robotics. Not very much is known regarding computational functions that the central nervous system performs in order to provide a set of requirements for visually-driven reaching and grasping. Additionally, in spite of several decades of advances in the field, the abilities of humanoids to perform similar tasks are by far modest when needed to operate in unstructured and dynamically changing environments. More specifically, our first focus is understanding the principles involved in human visuomotor coordination. Not many behavioral studies considered visuomotor coordination in natural, unrestricted, head-free movements in complex scenarios such as obstacle avoidance. To fill this gap, we provide an assessment of visuomotor coordination when humans perform prehensile tasks with obstacle avoidance, an issue that has received far less attention. Namely, we quantify the relationships between the gaze and arm-hand systems, so as to inform robotic models, and we investigate how the presence of an obstacle modulates this pattern of correlations. Second, to complement these observations, we provide a robotic model of visuomotor coordination, with and without the presence of obstacles in the workspace. The parameters of the controller are solely estimated by using the human motion capture data from our human study. This controller has a number of interesting properties. It provides an efficient way to control the gaze, arm and hand movements in a stable and coordinated manner. When facing perturbations while reaching and grasping, our controller adapts its behavior almost instantly, while preserving coordination between the gaze, arm, and hand. In the third part of the thesis, we study the neuroscientific literature of the primates. We here stress the view that the cerebellum uses the cortical reference frame representation. The cerebellum by taking into account this representation performs closed-loop programming of multi-joint movements and movement synchronization between the eye-head system, arm and hand. Based on this investigation, we propose a functional architecture of the cerebellar-cortical involvement. We derive a number of improvements of our visuomotor controller for obstacle-free reaching and grasping. Because this model is devised by carefully taking into account the neuroscientific evidence, we are able to provide a number of testable predictions about the functions of the central nervous system in visuomotor coordination. Finally, we tackle the flow of the visuomotor coordination in the direction from the arm-hand system to the visual system. We develop two models of motor-primed attention for humanoid robots. Motor-priming of attention is a mechanism that implements prioritizing of visual processing with respect to motor-relevant parts of the visual field. Recent studies in humans and monkeys have shown that visual attention supporting natural behavior is not exclusively defined in terms of visual saliency in color or texture cues, rather the reachable space and motor plans present the predominant source of this attentional modulation. Here, we show that motor-priming of visual attention can be used to efficiently distribute robot's computational resources devoted to visual processing.

A behavior strategy of humanoid robot for obstacle avoidance based on four infrared sensors is proposed and implemented on an autonomous humanoid robot. A mechanical structure with 26 degrees of freedom is design so that an implemented small-size humanoid robot named TWNHR-Ⅲ is able to accomplish five walking motions. Three walking experiments are presented to illustrate that the proposed biped structure lets TWNHR-Ⅲ can move forward, turn, and slip. One electronic compass and four infrared sensors are mounted on TWNHR-Ⅲ to obtain the head direction of the robot and detect obstacles, respectively. Based on the obtained information from these sensors, a decision tree method is proposed to decide one behavior from five movements: walk forward, turn right and left, and slip right and left. Two MATLAB simulations and one real experiment are presented to illustrate that the robot can avoid obstacles autonomously and go to the destination effectively.

In the present work a detailed study is presented, on the design, programming, and investigation of the behavior of flocking (Movement type flock), through the model of BOIDS, for its acronym in English "Bird Oid Object" (Object type bird), which was devised by Craig Reynolds in 1986. This complex flocking behavior that occurs arises from the interaction of simple local rules, in which complexity and sensitivity to initial conditions are present. A measure of chaotic compound will be introduced to the algorithm by means of a new four-dimensional autonomous hyperchaotic system based on the 3D Méndez-Arellano-Cruz-Martínez (MACM) system. The measures proposed herein, therefore, may have the potential to predict, control, and exemplify the behavior of group intelligence study systems that occur in nature, allowing the implementation of these systems in groups of robots through the implementation of hyperchaotic trajectories in the future, to obtain greater speed and efficiency, obstacle and collisions avoidance in their flights.

In this paper, we propose a novel evolutionary algorithm(EA)-based formation control with collision avoidance for nonholonomic mobile robots. In most conventional approaches, multi-robot formation control problem with collision avoidance can be formulated as a constrained nonlinear optimization problem in model predictive control (MPC) framework. The conventional approaches, therefore, suffer from the computational complexity problem corresponding to an increase in the number of constraints. To address this problem, a novel collision avoidance strategy is proposed incorporating a particle swarm optimization (PSO), which is one of the EAs. Numerical simulations verify the effectiveness of the proposed approach.

In response to safety concerns pertaining to multi-UAV formation flights, a novel obstacle avoidance method based on an Improved Adaptive Artificial Potential field (IAAPF) is presented. This approach enhances UAV obstacle avoidance capabilities by utilizing segmented attraction potential fields refined with adaptive factors and augmented with virtual forces for inter-UAV collision avoidance. To further enhance the control and stability of multi-UAV formations, a Sliding Mode Control (SMC) method is integrated into the IAAPF-based obstacle avoidance framework. Renowned for its robustness and ability to handle system uncertainties and disturbances, the SMC method is combined with a feedback control system that utilizes inner and outer loops. The outer loop generates the desired path based on the leader’s state and control commands, while the inner loop tracks these trajectories and adjusts the follower UAVs’ motions. This design ensures that obstacle feedback is accounted for before the desired state information is received, enabling effective obstacle avoidance while maintaining formation integrity. Integrating leader-follower formation control techniques with SMC-based multi-UAV obstacle avoidance strategies ensures the effective convergence of the formation velocity and spacing to predetermined values, meeting the cooperative obstacle avoidance requirements of multi-UAV formations. Simulation results validate the efficacy of the proposed method in reaching otherwise unreachable destinations within obstacle-rich environments, while ensuring robust collision avoidance among UAVs.

This paper considers formation control of a group of wheeled mobile robots with uncertainty. Decentralized cooperative robust controllers are proposed in two steps. In the first step, cooperative control laws are proposed for multiple kinematic systems with the aid of results from graph theory such that a group of robots comes into a desired formation. In the second step, cooperative robust control laws for multiple uncertain dynamic systems are proposed with the aid of backstepping techniques and the passivity properties of the dynamic systems such that multiple robots comes into a desired formation. Since communication delay is inevitable in cooperative control, its effect on the proposed controllers is analyzed. Simulation results show the effectiveness of the proposed controllers.